(2024) 22:320
Holdsworth‑Carson et al. BMC Medicine
https://doi.org/10.1186/s12916-024-03508-7

BMC Medicine

RESEARCH

Open AccessPredicting disease recurrence in patientswith endometriosis: an observational study
Sarah J. Holdsworth‑Carson1,2*, Jessica Chung1,3, Dorothy A. Machalek4,5, Rebecca Li1, Byung Kyu Jun1,
Meaghan J. Griffiths1, Molly Churchill1, Tristan McCaughey1, Debbie Nisbet6,7, Uri Dior8,
Jacqueline F. Donoghue1, Grant W. Montgomery9, Charlotte Reddington1, Jane E. Girling1,10,
Martin Healey1,2 and Peter A. W. Rogers1

Abstract
Background Despite surgical and pharmacological interventions, endometriosis can recur. Reliable information
regarding risk of recurrence following a first diagnosis is scant. The aim of this study was to examine clinical and sur‑vey data in the setting of disease recurrence to identify predictors of risk of endometriosis recurrence.
Methods This observational study reviewed data from 794 patients having surgery for pelvic pain or endometrio‑
sis. Patients were stratified into two analytic groups based on self-reported or surgically confirmed recurrent endo‑
metriosis. Statistical analyses included univariate, followed by multivariate logistic regression to identify risk factorsof recurrence, with least absolute shrinkage and selection operator (Lasso) regularisation. Risk-calibrated Supersparse
Linear Integer Models (RiskSLIM) and survival analyses (with Lasso) were undertaken to identify predictive featuresof recurrence.
Results Several significant features were repeatedly identified in association with recurrence, including adhesions,high rASRM score, deep disease, bowel lesions, adenomyosis, emergency room attendance for pelvic pain, younger
age at menarche, higher gravidity, high blood pressure and older age. In the surgically confirmed group, with a scoreof 5, the RiskSLIM method was able to predict the risk of recurrence (compared to a single diagnosis) at 95.3%
and included adenomyosis and adhesions in the model. Survival analysis further highlighted bowel lesions, adhesions
and adenomyosis.
Conclusions Following an initial diagnosis of endometriosis, clinical decision-making regarding disease manage‑
ment should take into consideration the presence of bowel lesions, adhesions and adenomyosis, which increase
the risk of endometriosis recurrence.
Keywords Endometriosis, Recurrent endometriosis, Endometriosis recurrence, Repeat surgery, Reoperation*Correspondence:
Sarah J. Holdsworth‑Carson
Sarah.Carson@epworth.org.au
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom‑mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

BackgroundThe symptoms and appearance of endometriosis areheterogeneous. Furthermore, the clinical manifestation and responsiveness to treatments can change overtime in individuals. This means there is no ‘one shoe fits
all’ approach to managing and treating endometriosis,
and in the absence of a failsafe cure, endometriosis disease recurrence is common (6–67%) [1–4]. Some previously reported risk factors for endometriosis recurrence
include severe or deep disease, younger age and conservative surgery with conservation of the ovaries anduterus [2]. Apprehension regarding recurrent disease ishigh among patients. ‘What is the most effective way of
stopping endometriosis progressing and/or spreading
to other organs (eg after surgery)?’ was listed in the top
10 endometriosis research priorities by consumers andhealth-care professionals in the UK and Ireland in 2017
[5].
Recurrence of endometriosis in an individual following complete surgical excision can be defined as lesion
recurrence on reoperation (with or without histologicalconfirmation) or on imaging. However, symptom-based
suspected recurrence, not proven by imaging and/or surgery, may also be considered a subtype of recurrent disease [6, 7]. With such broad definitions encapsulating
recurrent endometriosis, it is not surprising the reported
range of disease recurrence is so wide. Some limitations
that prevent findings from being replicated include failure to report the duration of follow-up (or short followup periods), examination of specific lesions types, forexample, endometrioma or deep lesions only, and failure
to report if excision was complete, thus bringing into
question the possibility of residual, rather than recurrent
disease [8]. Hence, the determinants for recurrence havenot been established and the true prevalence of endometriosis recurrence remains unknown.
To improve long-term health outcomes for patientswith endometriosis, it is important that we increase ourunderstanding of why endometriosis lesions return insome individuals and learn which risk factors contributeto the probability of the disease recurrence. The aim of
this study was to identify factors that are associated withincreased risk for recurrent disease, specifically lesions
returning, and to help predict probable risk of endometriosis recurrence.
Methods
Study design and participantsThis observational study was performed as a secondary
analysis of a prospective study (titled ‘Cellular, Molecularand Genetic Mechanisms of Endometriosis’), was performed according to the STROBE statement [9] and was
conducted with the consent of patients who were having

Page 2 of 35

laparoscopic surgery between May 2012 and March 2019at a tertiary university-affiliated referral centre (Royal
Women’s Hospital [RWH], Melbourne, Australia). In
this paper, the index surgery was considered to be thesurgery for which recruitment into the study occurred.
The study was approved by the Royal Women’s Hospital Human Research Ethics Committee (Project #1043, #11-24 and #16-43), which operates in accordancewith the National Health and Medical Research Council(NHMRC) National Statement on Ethical Conduct in
Human Research.
The total number of patients available for inclusion inthis study was n = 794. Patients were eligible for recruitment if they were English speaking, aged ≥ 18 years,
pre-menopausal, not pregnant and were undergoing laparoscopic surgery for investigation of pelvic pain and/or
treatment of endometriosis, usually with hysteroscopy,
dilation and curettage (unless prior hysterectomy) andcystoscopy. Medical information (including age, bloodpressure [BP] and body mass index [BMI]), surgicalreports, ultrasound reports, revised American Society for
Reproductive Medicine (rASRM) endometriosis scores[10] and pathology findings were collected. Surgeons also
filled out a study document providing further details on
lesions, including location (recorded as pouch of Douglas, uterovesical (UV) fold, bladder, bowel, fallopian tube,
pelvic side wall, pararectal space, uterosacral ligament
or other) and adhesions (presence yes/no). At each surgery, there was at least one surgeon with extensive experience with laparoscopic treatment of endometriosis. All
surgical reports were independently checked by a seniorspecialist laparoscopic surgeon (M.H.). Information collected from ultrasound reports included uterine volume,
uterine position, presence of fibroids (including numberof fibroids and volume of the largest fibroid), ovariancysts, polycystic ovaries and adenomyosis (including linear striations, heterogeneous myometrium and thickened
posterior wall). All collected ultrasound data were overseen by a senior ultrasound specialist (D.N.).
Participants completed a pre-surgery questionnaire
covering a range of self-reported gynaecological andnon-gynaecological variables. Gynaecological-related
variables included the following: a prior diagnosis ofendometriosis (prior to this index surgery), family history of endometriosis, age at menarche and pelvic pain
symptoms (dysmenorrhea, non-cyclical pelvic pain, dyspareunia or need to seek emergency room [ER] treatment
because of pain [prior to this index surgery]). Patients
reported pregnancies (gravidity), births (parity), current
hormone contraceptive use at the time of completing the
pre-surgery survey, previous diagnosis of ovarian cysts
and polycystic ovary disease, uterine fibroids, fibroticbreasts, adenomyosis, pre-cancer of the cervix (or anHoldsworth‑Carson et al. BMC Medicine(2024) 22:320

abnormal Papanicolaou test) and prior hysterectomy.
Allergic disorders commonly associated with endometriosis [11–13] were also recorded (presence of general foodallergies or intolerances, taste or smell disturbances, hay
fever and eczema). Patients were also asked to provide
tobacco smoking status (current, past or never).
Patients were stratified into two analytic groups basedon self-reported or surgically recorded recurrent endometriosis (Fig. 1):• Self-reported analysis
Patients who received a positive, pathology-confirmed,
endometriosis diagnosis at the referral centre (RWH)
were classified as having a single endometriosis diagnosis or recurrent endometriosis based on their survey
response to ‘Have you ever been diagnosed with endometriosis?’ (Yes = recurrent endometriosis; n = 221 or
No = single diagnosis of endometriosis; n = 302). Thoseclassified as a single diagnosis were further screenedusing hospital records, if they were found to have a diagnosis of endometriosis following a different surgery they
were removed (final number; n = 282). Those without any
record of surgically or pathology-confirmed endometriosis were classified as non-endometriosis controls (records
were also screened for evidence of endometriosis fromother laparoscopic surgeries) (n = 188).

Page 3 of 35• Surgically confirmed recurrence analysis
The hospital surgical records (RWH) of all participants
were screened to identify if participants had undergone
more than one surgery for endometriosis. For eachpotential case of recurrent endometriosis, the surgicalreports were vigorously examined to identify presence
and location of any residual disease at the surgery. As
no standardised format for recording untreated disease
exists in the surgical report format, complete text review
was undertaken of the reports (by T.M.). In the event ofknown residual disease (disease recorded as left behindor an abandoned surgery), recurrence was only assigned
if there was evidence that lesions had developed de novo
in the successive surgery (for example, in a new location
to that recorded in the previous report). Patients with
only evidence of residual disease were not included in therecurrent endometriosis group. Recurrent endometriosis, record of two or more surgeries where endometriosis
was visualised, was reported in n = 94. There were n = 288
participants grouped as having a single diagnosis ofendometriosis (one endometriosis positive surgery only
and no self-report of a previous endometriosis diagnosis), and n = 188 non-endometriosis controls. Note that
non-endometriosis control and single diagnosis groups
may have undergone more than one laparoscopy, but an
endometriosis diagnosis was not confirmed (control),Fig. 1 Flow chart illustrating the selection of participants in each analytic cohort. *There were n = 794 patients for inclusion in this study. Eachanalytic cohort was conducted independently; self-reported analysis or surgically confirmed analysis, and subjects crossed over into both cohorts

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

was only positive on one occasion (single diagnosis) or
was ruled out as being de novo growth (residual disease).
Data from available ultrasound reports and positiveor negative cervical intraepithelial neoplasia (CIN) findings on Papanicolaou test pathology screens were paired
to the closest surgical date. Ultrasound and CIN findings
were only available for participants who had these procedures undertaken at RWH.
Statistical analysis

Analysis was undertaken using the R programming language [14]. For both analyses, groups were first analysedusing univariate logistic regression for each variable
separately. Numerical variables were presented as means
and range, and binary and categorical variables were presented as n numbers and percentages, and as odds ratios(OR) with 95% confidence intervals (CI) with significancedenoted by p values < 0.05. For both analyses, a multivariate logistic regression with least absolute shrinkage andselection operator (Lasso) regularisation was performed
using the glmnet R package [15, 16], with test performance reported using receiver operating characteristic(ROC), sensitivity and specificity for each analysis. Variables with > 5% missing data were not included and variables with ≤ 5% missing values were imputed with either
the median value for numeric variables or most frequentvalue for non-numeric variables. The purpose of the multivariate Lasso model was to guide feature selection fora prediction model. Lasso analysis limits the number of
selected prognostic features remaining in a model bypenalising the absolute values of coefficients, resulting inshrinking some coefficients to zero.
Ultrasound data was included in the surgically confirmed endometriosis analysis, when available. As smaller
numbers were available, ultrasound data was analysed
independently using univariate regression analysis only,
and a Lasso regression and risk and survival analyses
were not undertaken on these data.
For both analyses, Risk-calibrated Supersparse Linear
Integer Models (RiskSLIM) were employed to create a
simple scoring system associated with the probability ofpatients developing recurrent disease [17]. The RiskSLIM
method uses optimisation techniques to find the best
logistic regression model with a limited number of risk
factors [18]. Variables with > 5% missing data were notincluded and the RiskSLIM model’s maximum numberof factors was limited to 5. Evaluation of the RiskSLIM
was performed by fivefold cross-validation (5-CV), wheredata was randomly split into 5 parts, fit using 4 of the 5folds, and validated on the last fold. This was repeated
5 times to estimate the area under the curve (AUC) andrisk calibration [18].

Page 4 of 35

For the surgically confirmed endometriosis analysis,time gap between surgical procedures was used to conduct a survival analysis that determined the impact ofvariables on the risk of recurrent endometriosis versus
a single diagnosis of endometriosis. Using the survival R
package [19], Cox proportional hazards ratios (HR) (95%
CI) were calculated to measure the effect of the hazard
rate (adjusted p values < 0.05 were considered significant).
Data was also presented as survival curves generatedusing the survminer R package [20], and fixed timepoints of 2 and 5 years post index surgery were tabulated(Kaplan–Meier p values of < 0.05 considered significant).
Multivariate Lasso analysis was employed to determine
which combination of variables provided a good model
for prediction.
Role of the funding sourceThis work was partially supported by National Healthand Medical Research Council (NHMRC) Grants
GNT1105321 and GNT1012245 (P.A.W.R., G.W.M.,
J.E.G., S.J.H-C.), GNT1026033 (G.W.M.) and NHMRC
Medical Research Future Fund GNT1199715 (P.A.W.R.,
M.H., S.J.H-C. and J.F.D.). G.W.M. was supported by
NHMRC Fellowships GNT1078399 and GNT1177194.
NHMRC played no role in the study design; in the collection, analysis and interpretation of data; in the writingof the report; or in the decision to submit the paper for
publication.

Results
Table 1 presents the results for the analysis of selfreported endometriosis recurrence. Tables 2 and 3
present the results for the surgically confirmed endometriosis recurrence analysis.
Common features of endometriosis that were associatedwith recurrent disease

Several endometriosis-related features were repeatedly identified in association with recurrent disease. The
recurrent endometriosis groups had increased odds of
having adhesions visualised at the index surgery compared to the group with a single endometriosis diagnosis,
in both the self-reported (Table 1) and surgically classified analysis (Table 2) (univariate OR 2.96 [95% CI 2.05–
4.26] and OR 3.17 [1.96–5.14], both p values < 0.001).
Adhesions detected at ultrasound prior to the index surgery were also significantly associated with recurrent disease compared to the single diagnosis group (univariate
OR 5.19 [1.91–14.13], p value 0.001) and controls (univariate OR 19.81 [2.54–154.74], p value 0.004) (Table 3).
Higher rASRM scores were associated with recurrent disease versus a single diagnosis in both analyses (univariate p values < 0.001) (Tables 1 and 2). In the59 (20.9)

35+ (n, %)77 (41.0)

49 (26.1)

110 (58.5)

182 (64.8)

46 (16.4)

12–14 (n, %) 121 (64.4)

15+ (n, %)24 (10.9)134 (60.6)

63 (28.5)

12.50 (8–17)

221

127 (57.5)

94 (42.5)

61 (27.6)

160 (72.4)

94 (42.5)

127 (57.5)

82 (37.1)

46 (20.8)55 (24.9)

38 (17.2)

31.79 (18–47)

221

Recurrent
endometriosis

0.90(0.44–1.81)

0.83(0.53–1.30)–

0.96(0.65–1.42)–

1.08(0.70–1.68)–

1.07(0.72–1.58)–

3.32(1.91–5.75)

1.96(1.09–3.52)

2.03(1.15–3.56)–

OR, 95% CI

0.758

0.406

0.655

0.831

0.727

0.747

< 0.001

0.025

0.014

< 0.001

0.000

0.000

0.000

0.000

0.000

0.641

0.000

0.000

p value Coef

2.04
(1.06–3.93)

1.33(0.85–2.10)–

1.23(0.84–1.80)

0.82(0.53–1.25)

0.83(0.57–1.21)

1.24(0.74–2.09)

1.24(0.73–2.10)

1.80(1.10–2.94)–

OR (95% CI)

0.033

0.215

0.025

0.279

0.354

0.333

0.416

0.428

0.018

0.862

0.150

0.000

0.000

−0.153

0.000

0.484

0.000

0.270

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

0.44(0.24–0.81)

0.62(0.40–0.95)–

0.78(0.54–1.11)–

1.33(0.88–1.99)–

1.29(0.90–1.84)–

2.67(1.59–4.47)

1.58(0.91–2.74)

1.12(0.67–1.88)–

OR (95% CI)

Multivariate
Lasso

0.009

0.028

0.006

0.171

0.175

0.171

< 0.001

0.106

0.656

< 0.001−0.302−0.116

0.000

0.230

0.000

0.223

0.000

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

20 (10.6)

53 (18.9)47 (25.0)

Under 12(n, %)

12.93 (8–19)

281

12.57 (8–16)

188

179 (63.5)

103 (36.5)

63 (22.3)

219 (77.7)

103 (36.5)

Mean(range)n

Age of menarche (years)a78 (41.5)

No (n, %)Yes (n, %)Never smokeda

139 (73.9)

No (n, %)Yes (n, %)Current smokera

111 (59.0)

No (n, %)Yes (n, %)179 (63.5)

56 (19.9)

30–34 (n, %) 39 (20.7)

Past smokera

94 (33.3)

41 (21.8)

73 (25.9)

29.17 (18–47)

282

25–29 (n, %) 45 (23.9)

29.05 (18–50)

188

Singleendometriosis
diagnosis

18–24 (n, %) 63 (33.5)

Mean(range)nAge (years)

Nonendometriosis
control

Table 1 Univariate and multivariate logistic regression results for the self-reported recurrent endometriosis analysis

Holdsworth‑Carson et al. BMC Medicine
Page 5 of 35

37 (19.7)

36 (19.1)

1–2

3+

135 (71.8)

39 (20.7)

14 (7.4)

0

1–2

3+

40 (21.5)

20 (10.8)

11 (5.9)

130–139140+

12 (4.3)

19 (6.7)

69 (24.5)

182 (64.5)

114.60 (82–158)282

3 (1.1)27 (9.6)

251 (89.3)

0.17 (0–4)

281

8 (2.8)65 (23.1)

208 (74.0)

0.42 (0–5)

281Singleendometriosis
diagnosis

73.16 (50–100)

186

73.16 (48–106)282
74.72 (43–101)

221

16 (7.2)

32 (14.5)42 (19.0)

131 (59.3)

117.5 (85–152)

221

6 (2.7)58 (26.2)

157 (71.0)

0.47 (0–4)

221

24 (10.9)

62 (28.1)

135 (61.1)

0.80 (0–6)

221

Recurrent
endometriosis

1.28(0.57–2.86)

1.40(0.76–2.59)

0.92(0.56–1.52)–

0.37(0.14–0.99)

1.28(0.80–2.04)–

0.57(0.32–1.01)

1.43(0.89–2.30)–

OR, 95% CI

0.127

0.553

0.277

0.750

0.344

0.047

0.302

0.298

0.053

0.144

0.046

0.000

0.000

0.000

−0.4230.000−0.5300.000

p value Coef

0.69
(0.29–1.61)

0.60(0.31–1.17)

1.09(0.69–1.72)–

0.12(0.03–0.41)

0.37(0.22–0.63)–

0.12(0.06–0.27)

0.97(0.61–1.54)–

OR (95% CI)

1.000

0.391

0.135

0.710

0.192

0.001

< 0.001< 0.001< 0.001

0.902< 0.001

0.000−0.1650.115−0.115−0.519−1.7970.000

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

1.85(0.85–4.05)

2.34(1.27–4.31)

0.85(0.54–1.32)–

3.20(0.79–12.97)

3.43(2.09–5.65)–

4.62(2.02–10.59)

1.47(0.98–2.21)–

OR (95% CI)

Multivariate
Lasso

0.083

0.122

0.006

0.460

0.015

0.104

<0.001< 0.001< 0.001

0.066< 0.001

0.174

0.480

−0.115

0.000

0.629

0.658

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

Mean(range)nDiastolic blood pressure (mmHg)

115 (61.8)

120–129116.20 (89–159)

186

Under 120Mean(range)nSystolic blood pressure (mmHg)

0.56 (0–5)

Mean(range)n

188

115 (61.2)

0Paritya1.12 (0–11)

188

Mean
(range)nGravidityaNonendometriosis
control

Table 1 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 6 of 35

13 (7.0)

9 (4.8)

85–89

90+

64 (22.7)

34 (12.1)

49 (26.1)

50 (26.6)

Pre-obese(25–29.9 kg/
m2)

Obese
(≥ 30 kg/m2)

177 (94.1)

268 (95.0)

160 (85.1)

38 (20.2)

150 (79.8)

Yes (n, %)210 (74.5)

72 (25.5)

226 (80.1)

56 (19.9)

174 (78.7)

47 (21.3)

187 (84.6)

34 (15.4)

208 (94.1)

13 (5.9)34 (15.4)

55 (24.9)8 (3.6)124 (56.1)

25.35 (17.23–
50.44)

221

22 (10.0)

20 (9.0)33 (14.9)

146 (66.1)

Recurrent
endometriosis

0.94(0.58–1.52)

0.96(0.56–1.66)

0.99(0.43–2.27)

0.48(0.29–0.80)

0.79(0.49–1.26)

2.81 (0.58–
13.54)–

2.19(0.98–4.93)

1.38(0.66–2.88)

0.90(0.52–1.54)

OR, 95% CI

0.793

0.890

0.989

0.005

0.322

0.199

0.018

0.058

0.391

0.692

0.000

0.000

0.000

−0.542

0.000

0.000

0.126

0.000

0.000

p value Coef

0.74
(0.47–1.15)

0.71(0.43–1.16)

1.19(0.53–2.68)

0.35(0.21–0.58)

0.67(0.42–1.05)

3.58(0.80–16.12)–

1.05(0.45–2.47)

0.73(0.34–1.58)

0.84(0.51–1.39)–

OR (95% CI)

0.183

0.170

0.675

< 0.001

0.081

0.096

< 0.001

0.912

0.419

0.495

−0.101−0.1760.000−0.956−0.140

0.670

0.133

0.000

0.000

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

1.27(0.83–1.93)–

1.36(0.85–2.18)–

0.84(0.38–1.82)–

1.37(0.81–2.33)

1.18(0.77–1.81)

0.78(0.32–1.92)

2.09(1.05–4.16)

1.90(0.94–3.83)

1.07(0.65–1.76)

OR (95% CI)

Multivariate
Lasso

0.265

0.195

0.651

0.242

0.453

0.595

0.099

0.036

0.073

0.794

0.014

0.013

−0.100

0.000

0.000

−0.415

0.061

0.000

−0.047p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

No (n, %)Dyspareuniaa

28 (14.9)

No (n, %)Yes (n, %)Severe pelvic pain (non-menstrual)a11 (5.9)

No (n, %)Yes (n, %)14 (5.0)

14 (5.0)

2 (1.1)

Under‑
weight(< 18.5 kg/m2)

Severe menstrual paina

170 (60.3)

87 (46.3)

Normal(18.5–24.9 kg/
m2)

24.56 (15.43–
47.9)

26.71 (16.05–
49.02)

282

15 (5.3)

15 (5.3)

44 (15.6)

208 (73.8)

Singleendometriosis
diagnosis

Mean(range)n

188

33 (17.7)

80–84

BMI (kg/m2)

131 (70.4)

Under 80

Nonendometriosis
control

Table 1 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 7 of 35

Singleendometriosis
diagnosisaRecurrent
endometriosis

57 (30.3)

110 (39.0)

172 (61.0)

93 (49.5)

1 (0.5)80 (42.7)

12 (6.4)

19 (10.1)

40 (21.3)

181 (96.3)

7 (3.7)No (n, %)Yes (n, %)Adenomyosisa

148 (78.7)

No (n, %)Yes (n, %)Polycystic ovary diseasea

169 (89.9)

No (n, %)Yes (n, %)Uterine fibroidsa

176 (93.6)

No (n, %)Yes (n, %)Fibrocystic breastsa

108 (57.4)

No (n, %)Yes (n, %)Ovarian cystsa

187 (99.5)

No (n, %)Yes (n, %)Previous hysterectomya

95 (50.5)

No (n, %)Yes (n, %)40 (18.1)

181 (81.9)

44 (19.9)

177 (80.1)

30 (13.6)

191 (86.4)

15 (6.8)206 (93.2)

135 (61.1)

86 (38.9)5 (2.3)216 (97.7)

87 (39.4)

134 (60.6)

126 (57.0)

95 (43.0)

5.71 (2.49–
13.09)

0.92(0.57–1.49)

1.40(0.76–2.57)

1.07(0.49–2.34)

2.12(1.43–3.15)

4.33 (0.50–
37.38)

0.66(0.45–0.98)

3.05(2.02–4.59)

OR, 95% CI< 0.001

0.733

0.283

0.870

< 0.001

0.183

0.041

< 0.001

0.908

0.000

0.000

0.000

0.320

0.000

−0.2160.872

p value Coef

1.25
(0.49–3.19)

0.84(0.53–1.33)

0.40(0.19–0.84)

0.71(0.32–1.59)

1.24(0.85–1.80)

0.60(0.41–0.87)

1.47(0.99–2.18)

OR (95% CI)

0.642

0.448

0.015

0.403

0.257

N/A

0.007

0.054

0.246

0.000

−0.511−0.5050.000

N/A−0.5430.463

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

4.57(2.38–8.79)–

1.10(0.70–1.72)–

3.53(1.76–7.08)–

1.51(0.70–3.24)–

1.71(1.20–2.44)–

1.11(0.77–1.60)–

2.07(1.45–2.97)–

OR (95% CI)

Multivariate
Lasso< 0.001

0.677<0.001

0.293

0.003

N/A

0.568

< 0.001

0.759

0.000

0.524

0.000

0.000

N/A

0.183

0.574

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

13 (4.6)

269 (95.4)

52 (18.4)

230 (81.6)

12 (4.3)

270 (95.7)

13 (4.6)

269 (95.4)

135 (47.9)

147 (52.1)

0 (0.0)282 (100.0)

104 (36.9)

178 (63.1)

Currently taking hormone medicationa

131 (69.7)

No (n, %)Yes (n, %)Attendance at an emergency room for menstrual/pelvic pain

Nonendometriosis
control

Table 1 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 8 of 35

Singleendometriosis
diagnosisaRecurrent
endometriosis

8 (4.3)45 (23.9)

15 (8.0)

No (n, %)42 (22.3)

90 (31.9)

192 (68.1)

106 (37.6)

176 (62.4)

15 (5.3)

267 (94.7)

66 (23.4)

216 (76.6)

14 (5.0)268 (95.0)

0 (0.0)14.6 (1–134)

282

70 (24.8)

211 (74.8)

0 (0.0)282 (100.0)

27.39 (1–142)

221

72 (32.6)

149 (67.4)

221 (100.0)

0 (0.0)47 (21.3)

174 (78.7)

105 (47.5)

116 (52.5)

26 (11.8)

195 (88.2)

66 (29.9)

155 (70.1)

13 (5.9)208 (94.1)

1.39(0.90–2.14)

0.94(0.59–1.50)

1.17(0.79–1.73)

1.54(0.79–3.00)

1.35(0.87–2.10)

1.41(0.57–3.47)

OR, 95% CI

N/A

0.136

N/A

0.793

0.431

0.207

0.180

0.459

0.047

N/A

0.000

0.000

0.000

0.000

0.000

p value Coef

0.95
(0.62–1.46)

1.63(1.07–2.49)

0.78(0.53–1.13)

0.65(0.31–1.36)

0.97(0.63–1.50)

1.18(0.48–2.86)

OR (95% CI)

N/A

0.827

N/A

0.024

0.192

0.251

0.894

0.722

0.000

N/A

0.340

−0.266

0.000

0.000

0.000

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

1.46(0.99–2.15)–

0.58(0.38–0.87)–

1.50(1.05–2.15)–

2.37(1.22–4.60)–

1.39(0.94–2.08)–

1.20(0.55–2.60)–

OR (95% CI)

Multivariate
Lasso< 0.001

0.059

N/A

0.008

0.025

0.010

0.103

0.651

0.000

0.369

N/A

−0.565

0.376

0.173

0.313

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

Mean(range)n

N/A

48 (25.8)

rASRM score

138 (74.2)

No (n, %)Yes (n, %)Family history of endometriosisa

188 (100.0)

No (n, %)Yes (n, %)Previous diagnosis of endometriosisa

Yes (n, %)146 (77.7)

82 (43.6)

Eczemaa106 (56.4)

No (n, %)Yes (n, %)Hay fevera

173 (92.0)

No (n, %)Yes (n, %)Disturbance to taste or smella

143 (76.1)

No (n, %)Yes (n, %)Food allergies or intolerancesa

180 (95.7)

No (n, %)Yes (n, %)Pre-cancer of the cervix or an abnormal Papanicolaou test

Nonendometriosis
control

Table 1 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 9 of 35

34 (12.1)

Stage 4(n, %)

93 (33.0)

37 (13.1)

63 (22.3)

250 (88.7)

79 (28.0)

123 (43.6)

159 (56.4)

N/A

No (n, %)122 (55.2)

99 (44.8)

96 (43.4)

125 (56.6)

173 (78.3)

48 (21.7)

80 (36.2)

141 (63.8)

23 (10.4)

198 (89.6)

131 (59.3)

90 (40.7)64 (29.0)

35 (15.8)

34 (15.4)

88 (39.8)

Recurrent
endometriosis

OR, 95% CI

N/A

N/A

N/A

N/A

N/A

N/A

N/A

p value Coef

OR (95% CI)

N/A

N/A

N/A

N/A

N/A

N/A

N/A

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

0.95(0.67–1.36)

1.97(1.36–2.86)

0.46(0.28–0.75)

1.97(1.33–2.92)

0.77(0.44–1.34)

2.96(2.05–4.26)

3.74(2.30–6.10)

2.32(1.34–4.02)

1.57(0.94–2.64)–

OR (95% CI)

Multivariate
Lasso

0.792

< 0.001

0.002

0.001

0.352

< 0.001< 0.001

0.003

0.087

0.000

0.290

−0.002

0.000

0.000

0.637

0.278

0.033

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

Yes (n, %)Pouch of Douglas

203 (72.0)

N/A

No (n, %)Yes (n, %)Deep peritoneal lesion(s)32 (11.3)

N/A

No (n, %)Yes (n, %)Superficial peritoneal lesion(s)219 (77.7)

N/A

No (n, %)Yes (n, %)Deep ovarian lesion(s)245 (86.9)

N/A

No (n, %)Yes (n, %)Superficial ovarian lesion(s)189 (67.0)

No (n, %)Yes (n, %)N/A

30 (10.6)

Stage 3(n, %)

Adhesions43 (15.2)

Stage 2(n, %)

N/A

175 (62.1)

Singleendometriosis
diagnosis

Stage 1(n, %)

Stage of endometriosis (rASRM)

Nonendometriosis
control

Table 1 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 10 of 35

192 (68.1)

43 (15.2)

Patient reported variable

73 (25.9)

75 (33.9)

146 (66.1)

98 (44.3)

123 (55.7)

18 (8.1)

203 (91.9)

148 (67.0)

73 (33.0)

12 (5.4)

209 (94.6)

45 (20.4)

176 (79.6)

5 (2.3)216 (97.7)

54 (24.4)

167 (75.6)

Recurrent
endometriosis

OR, 95% CI

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

p value Coef

OR (95% CI)

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

1.47(1.00–2.16)

0.92(0.64–1.31)

0.49(0.28–0.88)

0.95(0.65–1.38)

1.02(0.47–2.23)

2.00(1.22–3.27)

6.50(0.75–56.08)

0.94(0.63–1.42)

OR (95% CI)

Multivariate
Lasso

0.050

0.637

0.017

0.791

0.956

0.006

0.088

0.778

0.000

0.000

−0.5470.000−0.109

0.000

0.716

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320a

209 (74.1)

No (n, %)Yes (n, %)N/A131 (46.5)

Other

151 (53.5)

N/A

No (n, %)Yes (n, %)Uterosacral ligament

239 (84.8)

N/A

No (n, %)Yes (n, %)Pararectal space

90 (31.9)

No (n, %)Yes (n, %)N/A

15 (5.3)

Pelvic side wall

267 (94.7)

No (n, %)Yes (n, %)N/A

32 (11.3)

Tube

250 (88.7)

No (n, %)Yes (n, %)N/A

1 (0.4)Bowel

281 (99.6)

No (n, %)Yes (n, %)N/A

72 (25.5)

Bladder

210 (74.5)

N/A

No (n, %)Singleendometriosis
diagnosis

Yes (n, %)UV pouch

Nonendometriosis
control

Table 1 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 11 of 35

188

288

61 (21.2)

35+ (n, %)77 (41.0)

Yes (n, %)183 (63.8)

48 (16.7)

12–14 (n, %) 121 (64.4)

15+ (n, %)7 (7.4)63 (67.0)

24 (25.5)

12.46 (9–17)

94

46 (48.9)

48 (51.1)

28 (29.8)

66 (70.2)

48 (51.1)

46 (48.9)30 (31.9)25 (26.6)

22 (23.4)

17 (18.1)

31.26 (18–45)

94

Recurrent
endometriosis

0.69(0.25–1.85)

1.02(0.57–1.82)–

0.68(0.41–1.12)

1.20(0.69–2.08)

1.50(0.91–2.48)

2.71(1.33–5.53)

2.38(1.14–4.95)

1.81(0.86–3.80)–

OR (95% CI)

0.455

0.947

0.554

0.128

0.509

0.108

0.006

0.021

0.115

0.017

0.000

0.000

0.000

0.000

0.000

0.131

0.000

0.000

p value Coef

2.01
(1.05–3.86)

1.27(0.81–1.99)–

1.20(0.82–1.75)

0.86(0.56–1.32)

0.85(0.58–1.24)

1.23(0.73–2.07)

1.19(0.70–2.02)

1.75(1.08–2.85)–

OR (95% CI)

0.035

0.300

0.030

0.343

0.487

0.405

0.427

0.518

0.024

0.854

0.186

0.000

0.019

−0.066

0.000

0.353

0.000

0.219

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

0.34(0.13–0.86)

0.80(0.46–1.40)–

0.57(0.35–0.91)

1.40(0.83–2.35)

1.77(1.10–2.82)

2.20(1.11–4.36)

2.00(0.98–4.04)

1.04(0.51–2.09)–

OR (95% CI)

Multivariate
Lasso

0.023

0.441

0.025

0.018

0.205

0.018

0.024

0.055

0.923

0.008

−0.435

0.000

0.000

0.000

0.317

0.000

0.000

−0.027p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

20 (10.6)

56 (19.5)

47 (25.0)

Under 12(n, %)

287

12.92 (8–19)

12.57 (8–16)

188

181 (62.8)

107 (37.2)

67 (23.3)

221 (76.6)

107 (37.2)

Mean(range)n

Age of menarche (years)a78 (41.5)

110 (58.5)

No (n, %)Yes (n, %)Never smokeda

139 (73.9)

49 (26.1)

No (n, %)Yes (n, %)Current smokera

111 (59.0)

No (n, %)181 (62.8)

56 (19.4)

30–34 (n, %) 39 (20.7)

Past smokera

95 (33.0)

41 (21.8)

76 (26.4)

29.17 (18–47)

25–29 (n, %) 45 (23.9)

29.05 (18–50)

Singleendometriosis
diagnosis

18–24 (n, %) 63 (33.5)

Mean(range)nAge (years)

Nonendometriosis
control

Table 2 Univariate and multivariate logistic regression results for the surgically confirmed recurrent endometriosis analysis

Holdsworth‑Carson et al. BMC Medicine
Page 12 of 35

36 (19.1)

3+

135 (71.8)

39 (20.7)

14 (7.4)

0

1–2

3+

186

40 (21.5)

20 (10.8)

11 (5.9)

130–139140+

12 (4.2)

19 (6.6)

69 (24.0)

188 (65.3)

114.40 (82–158)288

3 (1.0)29 (10.1)

255 (88.9)

0.18 (0–4)

287

8 (2.8)69 (24.0)

210 (73.2)

0.43 (0–5)

287Singleendometriosis
diagnosis

Mean(range)18673.16 (50–100)

288

72.94 (48–106)

74.63 (43–100)

93

8 (8.6)13 (14.0)

13 (14.0)

59 (63.4)

117.70 (90–152)

93

2 (2.1)24 (25.5)

68 (72.3)

0.42 (0–3)

94

9 (9.6)29 (30.9)

56 (59.6)

0.78 (0–5)

94

Recurrent
endometriosis

1.42(0.54–3.71)

1.27(0.59–2.72)

0.63(0.31–1.28)–

0.28(0.06–1.28)

1.22(0.68–2.20)–

0.51(0.23–1.14)

1.61(0.90–2.88)–

OR (95% CI)

0.263

0.478

0.545

0.201

0.414

0.102

0.503

0.227

0.101

0.109

0.109

0.000

0.000

0.000

−0.0480.000−0.3660.000

p value Coef

0.67
(0.29–1.56)

0.58(0.30–1.14)

1.06(0.67–1.66)–

0.11(0.03–0.40)

0.39(0.23–0.66)–

0.12(0.05–0.27)

1.02(0.65–1.62)–

OR (95% CI)

0.816

0.351

0.112

0.816

0.136

0.001

< 0.001< 0.001< 0.001

0.929< 0.001

0.000−0.154

0.076

0.000

−0.485−1.7460.000

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

2.12(0.83–5.44)

2.18(1.02–4.68)

0.60(0.31–1.16)–

2.50(0.41–15.26)

3.10(1.70–5.67)–

4.22(1.56–11.43)

1.58(0.93–2.66)–

OR (95% CI)

Multivariate
Lasso

0.157

0.117

0.045

0.130

0.039

0.321

< 0.001

0.002

0.005

0.089

0.003

0.000

0.003

−0.344

0.000

0.345

0.535

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320nDiastolic blood pressure (mmHg)

115 (61.8)

120–129116.20 (89–159)

Under 120Mean(range)nSystolic blood pressure (mmHg)

0.56 (0–5)

nMean(range)188

37 (19.7)

1–2

Paritya

115 (61.2)

0188

1.12 (0–11)

Mean(range)nGravidityaNonendometriosis
control

Table 2 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 13 of 35

9 (4.8)

90+

66 (22.9)35 (12.2)

49 (26.1)

50 (26.6)

Pre-obese(25–29.9 kg/
m2)

Obese
(≥ 30 kg/m2)

268 (93.1)

38 (20.2)

150 (79.8)

Yes (n, %)62 (21.5)210 (72.9)

78 (27.1)

226 (78.5)

74 (78.7)

20 (21.3)

81 (86.2)

13 (13.8)

89 (94.7)

5 (5.3)23 (24.5)

22 (23.4)

5 (5.3)44 (46.8)

26.22 (17.23–
50.44)

94

12 (12.9)

5 (5.4)12 (12.9)

64 (68.8)

Recurrent
endometriosis

0.94(0.51–1.72)

1.09(0.54–2.22)

1.11(0.37–3.28)

0.91(0.49–1.68)

0.89(0.48–1.65)

4.94 (0.92–
26.51)–

2.73(1.09–6.81)

0.79(0.27–2.30)

0.74(0.36–1.54)–

OR (95% CI)

0.835

0.811

0.856

0.762

0.707

0.062

0.513

0.031

0.662

0.425

0.000

0.000

0.000

0.000

0.000

0.000

0.087

0.000

0.000

p value Coef

0.68
(0.44–1.06)

0.64(0.39–1.04)

0.83(0.39–1.78)

0.35(0.21–0.58)

0.68(0.43–1.06)

3.52(0.78–15.84)–

1.02(0.43–2.40)

0.71(0.33–1.53)

0.82(0.49–1.35)

OR (95% CI)

0.089

0.072

0.637

< 0.001

0.090

0.101

< 0.001

0.963

0.379

0.427

−0.122−0.1900.000−0.885−0.108

0.539

0.000

0.000

0.000

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

1.37(0.79–2.40)

1.71(0.89–3.27)

1.33(0.48–3.64)

2.58(1.39–4.81)

1.31(0.73–2.35)

1.40(0.48–4.11)

2.67(1.19–6.01)

1.11(0.39–3.18)

0.91(0.45–1.83)–

OR (95% CI)

Multivariate
Lasso

0.264

0.106

0.581

0.003

0.365

0.535

0.011

0.017

0.840

0.795

0.000

0.107

0.000

0.217

0.000

0.000

0.217

0.000

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

No (n, %)Dyspareuniaa

28 (14.9)

160 (85.1)

No (n, %)Yes (n, %)Severe pelvic pain (non-menstrual)a11 (5.9)

177 (94.1)

No (n, %)Yes (n, %)20 (6.9)

14 (4.9)

2 (1.1)

Under‑
weight(< 18.5 kg/m2)

Severe menstrual paina

173 (60.1)

87 (46.3)

Normal(18.5–24.9 kg/
m2)

288

24.56 (15.43–
47.90)

26.71 (16.05–
49.02)n

15 (5.2)

15 (5.2)

44 (15.3)

214 (74.3)

Singleendometriosis
diagnosis

Mean(range)188

13 (7.0)

85–89

BMI (kg/m2)

131 (70.4)

33 (17.7)

Under 80

80–84

Nonendometriosis
control

Table 2 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 14 of 35

Singleendometriosis
diagnosisaRecurrent
endometriosis

178 (61.8)

110 (38.2)

181 (96.3)

7 (3.7)No (n, %)181 (62.8)

13 (4.5)275 (95.5)

52 (18.1)

236 (81.9)

12 (4.2)

276 (95.8)

13 (4.5)275 (95.5)

135 (46.9)

153 (53.)

0 (0.0)288 (100.0)

107 (37.2)

45 (47.9)

20 (21.3)

74 (78.7)

21 (22.3)

73 (77.7)

12 (12.8)

82 (87.2)

6 (6.4)88 (93.6)

56 (59.6)

38 (40.4)

4 (4.3)90 (95.7)

32 (34.0)

62 (66.0)

49 (52.1)

6.99 (2.83–
17.23)

1.06(0.59–1.94)

1.30(0.60–2.81)

1.00(0.36–2.75)

1.99(1.20–3.29)

8.31 (0.92–
75.44)

0.53(0.32–0.88)

2.50(1.50–4.17)

OR (95% CI)< 0.001

0.838

0.502

1.000

0.007

0.060

0.015

< 0.001

1.356

0.000

0.000

0.000

0.119

0.000

−0.2620.523

p value Coef

1.22
(0.48–3.12)

0.82(0.51–1.29)

0.39(0.18–0.82)

0.69(0.31–1.55)

1.19(0.82–1.73)

0.60(0.42–0.88)

1.42(0.96–2.10)

OR (95% CI)

0.675

0.385

0.013

0.374

0.355

N/A

0.008

0.079

0.217

0.000

−0.508−0.4140.000−0.4820.366

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

5.72(2.72–12.03)

1.31(0.74–2.31)

3.37(1.46–7.78)

1.44(0.53–3.91)

1.67(1.04–2.68)

0.87(0.54–1.42)

1.76(1.10–2.82)

OR (95% CI)

Multivariate
Lasso< 0.001

0.360

0.004

0.471

0.033

N/A

0.586

0.018

1.250

0.000

0.727

0.000

0.000

0.000

0.170

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

Yes (n, %)Adenomyosisa

148 (78.7)

40 (21.3)

No (n, %)Yes (n, %)Polycystic ovary diseasea

169 (89.9)

19 (10.1)

No (n, %)Yes (n, %)Uterine fibroidsa

176 (93.6)

12 (6.4)

No (n, %)Yes (n, %)Fibrocystic breastsa

108 (57.4)

80 (42.7)

No (n, %)Yes (n, %)Ovarian cystsa

187 (99.5)

1 (0.5)

No (n, %)Yes (n, %)Previous hysterectomya

95 (50.5)

93 (49.5)

No (n, %)Yes (n, %)Currently taking hormone medicationa

131 (69.7)

57 (30.3)

No (n, %)Yes (n, %)Attendance at an emergency room for menstrual/pelvic pain

Nonendometriosis
control

Table 2 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 15 of 35

Singleendometriosis
diagnosisaRecurrent
endometriosis

274 (95.1)

14 (4.9)85 (90.4)
9 (9.6)259 (89.9)

90 (31.3)

198 (68.8)

106 (36.8)

182 (63.2)

15 (5.2)

273 (94.8)

66 (22.9)

222 (77.1)

29 (10.1)

138 (74.2)

48 (25.8)

No (n, %)Yes (n, %)Family history of endometriosisa

188 (100.0)

0 (0.0)No (n, %)Yes (n, %)77 (81.9)30 (31.9)

64 (68.1)

75 (79.8)

19 (20.2)

22 (23.4)

72 (76.6)

49 (52.1)

45 (47.9)

12 (12.8)

82 (87.2)

28 (29.8)

66 (70.2)

17 (18.1)

1.35(0.78–2.32)

1.06(0.59–1.91)

1.41(0.86–2.31)

1.69(0.76–3.77)

1.35(0.77–2.35)

2.22(1.08–4.58)

2.38(0.89–6.39)

OR (95% CI)

0.282

N/A

0.841

0.177

0.202

0.291

0.031

0.085

0.000

0.000

0.199

0.000

0.000

0.184

0.000

p value Coef

0.96
(0.63–1.47)

1.58(1.03–2.41)

0.75(0.52–1.10)

0.63(0.30–1.33)

0.94(0.61–1.46)

1.13(0.60–2.11)

1.15(0.47–2.80)

OR (95% CI)

0.861

N/A

0.034

0.138

0.227

0.797

0.711

0.758

0.000

0.322

−0.255

0.000

0.000

0.000

0.000

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

1.40(0.84–2.33)

0.67(0.39–1.15)

1.87(1.17–2.99)

2.66(1.20–5.92)

1.43(0.85–2.40)

1.97(1.03–3.78)

2.07(0.87–4.96)

OR (95% CI)

Multivariate
Lasso

0.196

N/A

0.148

0.009

0.016

0.181

0.041

0.102

0.145

−0.279

0.460

0.203

0.127

0.456

0.339

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

72 (25.1)

215 (74.9)

0 (0.0)288 (100.0)

Previous diagnosis of endometriosisa

146 (77.7)

42 (22.3)

No (n, %)Yes (n, %)Eczemaa106 (56.4)

82 (43.6)

No (n, %)Yes (n, %)Hay fevera

173 (92.0)

15 (8.0)

No (n, %)Yes (n, %)Disturbance to taste or smella

143 (76.1)

45 (23.9)

No (n, %)Yes (n, %)Food allergies or intolerancesa

171 (91.0)

17 (9.0)

No (n, %)Yes (n, %)Cervical intraepithelial neoplasia (CIN) (pathology)

180 (95.7)

8 (4.3)

No (n, %)Yes (n, %)Pre-cancer of the cervix or an abnormal Papanicolaou test

Nonendometriosis
control

Table 2 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 16 of 35

N/A

32 (11.1)

256 (88.9)

N/A

No (n, %)Yes (n, %)Superficial peritoneal lesion(s)225 (78.1)

63 (21.9)

N/A

No (n, %)Yes (n, %)Deep ovarian lesion(s)251 (87.2)

37 (12.8)

No (n, %)N/A

191 (66.3)

97 (33.7)

Yes (n, %)Superficial ovarian lesion(s)150 (79.8)

38 (20.2)

No (n, %)Yes (n, %)Adhesions (surgical)

34 (11.8)30 (10.4)

Stage 3(n, %)

Stage 4(n, %)

42 (14.9)

Stage 2(n, %)N/A

181 (62.8)

14.32 (1–134)

288

Singleendometriosis
diagnosis

Stage 1(n, %)

Stage of endometriosis (rASRM)

Mean(range)nrASRM score

Nonendometriosis
control

Table 2 (continued)

75 (79.8)

19 (20.2)

24 (25.5)

70 (74.5)

16 (17.0)

78 (83.0)

58 (61.7)

36 (38.3)

26 (27.7)

12 (12.8)

20 (21.3)

36 (38.3)

27.45 (1–142)

94

Recurrent
endometriosis

6.36 (3.68–
10.99)OR (95% CI)

N/A

N/A

N/A

< 0.001

N/A

N/A

1.524

p value Coef

2.00
(1.30–3.09)

OR (95% CI)

N/A

N/A

N/A

0.002

N/A

N/A

0.408

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

0.49(0.26–0.92)

1.22(0.71–2.10)

1.39(0.73–2.64)

3.17(1.96–5.14)

3.84(2.06–7.17)

2.01(0.94–4.30)

2.34(1.23–4.43)–

OR (95% CI)

Multivariate
Lasso

0.026

0.463

0.311

< 0.001< 0.001

0.071

0.009

< 0.001

0.000−0.192

0.000

0.715

0.000

0.000

0.394

0.001

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320
Page 17 of 35

43 (14.9)

Yes (n, %)N/A

245 (85.1)
7 (7.4)87 (92.6)

62 (66.0)

32 (34.0)

8 (8.5)86 (91.5)

28 (29.8)

66 (70.2)

2 (2.1)92 (97.9)30 (31.9)

64 (68.1)

59 (62.8)

35 (37.2)

39 (41.5)

55 (58.5)

Recurrent
endometriosis

OR (95% CI)

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

p value Coef

OR (95% CI)

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

0.46(0.20–1.06)

0.94(0.57–1.54)

1.69(0.69–4.13)

3.39(1.91–6.03)

6.24(0.56–69.60)

1.38(0.83–2.30)

1.31(0.81–2.12)

1.88(1.15–3.05)

OR (95% CI)

Multivariate
Lasso

0.067

0.802

0.247

< 0.001

0.137

0.214

0.267

0.011

−0.371

0.000

0.000

0.691

0.699

0.008

0.000

0.000

p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis(2024) 22:320

No (n, %)Pararectal space

94 (32.6)

194 (67.4)

N/A

No (n, %)Yes (n, %)Pelvic side wall

273 (94.8)

15 (5.2)

N/A

No (n, %)Yes (n, %)Tubes

256 (88.9)

32 (11.1)

N/A

No (n, %)Yes (n, %)Bowel

287 (99.7)

1 (0.3)N/A

No (n, %)Yes (n, %)Bladder

215 (74.7)

73 (25.3)

N/A

No (n, %)Yes (n, %)UV pouch

126 (43.8)

162 (56.3)

N/A

No (n, %)Yes (n, %)Pouch of Douglas

209 (72.6)

79 (27.4)

N/A

No (n, %)Singleendometriosis
diagnosis

Yes (n, %)Deep peritoneal lesion(s)Nonendometriosis
control

Table 2 (continued)

Holdsworth‑Carson et al. BMC Medicine
Page 18 of 35

aPatient reported variable

215 (74.7)

73 (25.3)

N/A

No (n, %)Yes (n, %)Other

154 (53.5)

134 (46.5)

N/A

No (n, %)Singleendometriosis
diagnosis

Yes (n, %)Uterosacral ligament

Nonendometriosis
control

Table 2 (continued)

26 (27.7)

68 (72.3)

38 (40.4)

56 (59.6)

Recurrent
endometriosis

OR (95% CI)

N/A

N/A

p value Coef

OR (95% CI)

N/A

N/A

p value Coef

Multivariate
Lasso

Univariate analysis

Univariate analysis

Multivariate
Lasso

Non-endometriosis control vs single
endometriosis diagnosis

Non-endometriosis control vsrecurrent endometriosis

1.13(0.67–1.90)

0.78(0.49–1.25)

OR (95% CI)

Multivariate
Lasso

0.657

0.302

0.000

−0.074p value Coef

Univariate analysis

Single endometriosis diagnosis vsrecurrent endometriosis

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320
Page 19 of 35

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 20 of 35

Table 3 Univariate results for the surgically confirmed recurrent endometriosis analysis using ultrasound data
Nonendometriosis
control

SingleRecurrent
Non-endometriosis
endometriosis endometriosis control vs recurrent
diagnosis
endometriosis

Non-endometriosis
control vs single
endometriosis
diagnosis

Single endometriosis
diagnosis vs recurrent
endometriosis

Univariate analysis
OR, 95% CI

p value OR, 95% CI

p value OR, 95% CI

p value

0.119

0.672

0.017

Uterine volume (ml)nMean(range)

67

105

63

69.70 (16.00–
308.40)67.00 (23.00–
213.00)85.81 (23.20–
370.00)Under 40 ml 16 (23.9)

14 (13.3)

5 (7.9)40–110 ml

44 (65.7)

82 (78.1)

45 (71.4)

3.27 (1.10–9.70) 0.033

2.13 (0.95–4.77) 0.066

1.54 (0.52–
4.54)

0.437

> 110 ml7 (10.4)

9 (8.6)13 (20.6)

5.94 (1.52–
23.18)

0.010

1.47 (0.43–4.98) 0.537

4.04 (1.07–
15.27)

0.039

0.023

0.460

Log uterine volume (ml)nMean(range)

67

105

63

1.77 (1.20–2.49)

1.79 (1.36–2.33)

1.87 (1.37–2.57)

0.021

Uterine position
Anteverted

59 (90.8)

83 (79.8)

48 (77.4)

Retroverted

6 (9.2)20 (19.2)

12 (19.4)

2.46 (0.86–7.04) 0.094

2.37 (0.90–6.26) 0.082

1.04 (0.47–
2.31)

–
0.928

Axial

0 (0.0)1 (1.0)2 (3.2)

N/A

N/A

3.46 (0.31–
39.15)

0.316

2.04 (0.80–5.24) 0.137

0.99 (0.39–2.53) 0.990

2.05 (0.90–
4.68)

0.087

0.421

0.294

0.034

0.414

0.148

0.188

2.09 (1.01–4.34) 0.048

1.61 (0.83–3.14) 0.163

0.047

0.078

0.28 (0.07–1.07) 0.063

0.91 (0.38–2.14) 0.822

0.31 (0.09–
1.12)

0.073

4.40 (1.52–
12.73)

3.44 (1.25–9.49) 0.017

1.28 (0.63–
2.60)

0.498

Fibroids present
No (n, %)63 (88.7)

103 (88.8)

54 (79.4)

Yes (n, %)8 (11.3)

13 (11.2)

14 (20.6)

No. of fibroidsn
Mean(range)

71

116

68

0.23 (0–5)

0.13 (0–2)

0.34 (0–4)

Volume of largest fibroid (ml)nMean(range)6

11

1158.62 (0.40–
174.00)2.89 (0.10–8.00)

27.74 (0.60–
246.50)Ovarian cysts present
No (n, %)54 (76.1)

77 (66.4)

41 (60.3)

Yes (n, %)17 (23.9)

39 (33.6)

27 (39.7)

1.30 (0.70–
2.42)

0.407

No. of ovarian cystsnMean(range)

71

116

68

0.34 (0–4)

0.67 (0–10)

0.62 (0–3)

0.773

Polycystic ovaries present
No (n, %)61 (85.9)

101 (87.1)

65 (95.6)

Yes (n, %)10 (14.1)

15 (12.9)

3 (4.4)

Adenomyosis present
No (n, %)66 (93.0)

92 (79.3)

51 (75.0)

Yes (n, %)5 (7.0)24 (20.7)

17 (25.0)

0.006

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 21 of 35

Table 3 (continued)
Nonendometriosis
control

SingleRecurrent
Non-endometriosis
endometriosis endometriosis control vs recurrent
diagnosis
endometriosis

Non-endometriosis
control vs single
endometriosis
diagnosis

Single endometriosis
diagnosis vs recurrent
endometriosis

Univariate analysis
OR, 95% CI

p value OR, 95% CI

p value OR, 95% CI

p value

Adenomyosis linear striations present
No (n, %)68 (95.8)

105 (90.5)

62 (91.2)

Yes (n, %)3 (4.2)11 (9.5)

6 (8.8)2.19 (0.53–9.15) 0.281

2.37 (0.64–8.82) 0.197

0.92 (0.33–
2.62)

0.882

N/A

N/A

2.55 (0.78–
8.37)

0.123

Adenomyosis heterogeneous myometrium
No (n, %)71 (100.0)

111 (95.7)

61 (89.7)

Yes (n, %)0 (0.0)5 (4.3)7 (10.3)

Adenomyosis thickened posterior wall
No (n, %)68 (95.8)

105 (90.5)

61 (89.7)

Yes (n, %)3 (4.2)11 (9.5)

7 (10.3)

2.60 (0.64–
10.51)

0.180

2.37 (0.64–8.82) 0.197

1.10 (0.40–
2.97)

0.858

24.15 (5.46–
106.78)< 0.001

13.14(3.04–56.80)

0.001

1.84 (0.98–
3.46)

0.059

7.39 (1.59–
34.41)

0.011

1.23 (0.22–6.91) 0.812

6.00 (1.85–
19.45)

0.003

N/A

0.94 (0.30–
2.94)

0.920

5.19 (1.91–
14.13)

0.001

Endometriosis present (including OMA)
No (n, %)69 (97.2)

84 (72.4)

40 (58.8)

Yes (n, %)2 (2.8)32 (27.6)

28 (41.2)

Endometriosis present (excluding OMA)
No (n, %)69 (97.2)

112 (96.6)

56 (82.4)

Yes (n, %)2 (2.8)4 (3.4)12 (17.6)

Bilateral endometriomas
No (n, %)71 (100.0)

107 (92.2)

63 (92.6)

Yes (n, %)0 (0.0)9 (7.8)5 (7.4)N/A

Adhesions (ultrasound)
No (n, %)70 (98.6)

110 (94.8)

53 (77.9)

Yes (n, %)1 (1.4)6 (5.2)15 (22.1)

19.81 (2.54–
154.74)0.004

3.82 (0.45–
32.39)

0.219

OMA Endometrioma

self-reported analysis, this was emphasised in association with stage 4 disease (OR 3.74 [2.30–6.10], p value< 0.001) and subsequently, the reported presence of deep
peritoneal disease (OR 1.97 [1.36–2.86], p value < 0.001)(Table 1). Narrowing down, in the analysis using surgically classified recurrent disease, the presence of bowel
lesions was significantly linked to recurrence (OR 3.39
[1.91–6.03], p value < 0.001) (Table 2). In contrast, patientswith lesions in the pararectal space had a lower odds ofrecurrent endometriosis relative to having a single diagnosis of endometriosis (OR 0.49 [0.28–0.88], p value
0.017, and OR 0.46 [0.20–1.06], p value 0.067, respectively)(Tables 1 and 2).

Other gynaecological features associated with recurrent
endometriosis

Adenomyosis (patient reported), in both the self-reported
and surgically confirmed analyses, was associated with anincreased likelihood of endometriosis recurrence compared to a single diagnosis (Tables 1 and 2) (univariate
OR 4.57 [2.38–8.79] and OR 5.72 [2.72–12.03], both pvalues < 0.001, respectively). Those with surgically confirmed recurrence had increased odds of adenomyosis as
detected by ultrasound compared to controls (univariate
OR 4.40 [1.52–12.73], p value 0.006) (Table 3). Also ofnote in Table 3, uterine volume (logged) was increased in
the recurrent endometriosis group compared to controls

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

and those with a single diagnosis (p value 0.023 and 0.021,
respectively), which may be an indicator of adenomyosis.
Self-reported recurrent disease increased the odds forpresentation at an ER compared to controls and thosewith a single diagnosis (both p values < 0.001) (Table 1).
Similar outcomes were observed in the surgically confirmed analysis (Table 2), where recurrent endometriosis
was associated with increased odds of presenting to an
ER with pelvic pain (p values < 0.001 and 0.018). Dysmenorrhea, dyspareunia and severe (non-menstrual) pelvic
pain were not significantly associated with endometriosis
recurrence (Tables 1 and 2).
When comparing non-endometriosis controls to recurrent endometriosis cases, recurrent endometriosis was
associated with reduced odds of taking hormone medication (Tables 1 and 2) (p value 0.041 and p value 0.015,
respectively). However, this response was not limited torecurrent endometriosis, as those with a single endometriosis diagnosis were also found to have reduced odds ofhormone medication usage compared to non-endometriosis controls (Tables 1 and 2) (p value 0.007 and p value
0.008, respectively).
Older age at the time of first menstrual period (in particular 15 + years) was associated with the single diagnosis of endometriosis group compared to the recurrence orcontrol groups (Tables 1 and 2), albeit in opposite directions. Those with a single diagnosis of endometriosis
had an increased odds of being 15 + years at the time offirst menarche compared to non-endometriosis controls(Tables 1 and 2) (p value 0.033 and p value 0.035). However, the opposite effect was seen in the single diagnosis
versus recurrent endometriosis groups, where older age
at menarche (15 +) reduced the odds of recurrence relative to a single diagnosis of endometriosis (p value 0.009
and p value 0.023, respectively) (Tables 1 and 2).
Gravidity and parity were significantly associated with asingle or recurrent endometriosis diagnosis (Tables 1 and
2). A similar pattern was observed for the single diagnosis
group, which had reduced odds of reporting 3 + gravidity
compared to controls (p value < 0.001 and p value < 0.001,
respectively) (Tables 1 and 2), and reduced odds ofreporting a parity between 1 and 2 or 3 + compared

Page 22 of 35

to controls (p values also ranging between < 0.001 and0.001) (Tables 1 and 2). However, when comparing recurrent disease to a single diagnosis of endometriosis in bothanalytic groups (Tables 1 and 2), an increase of the odds
of reporting a gravidity of 3 + (p value < 0.001 and 0.005,
respectively) or a parity of 1–2 (p value, both < 0.001) was
observed.
Non‑gynaecological factors associated with endometriosis
recurrence

An obese BMI increased the likelihood of recurrence
when compared to a single diagnosis of endometriosis(univariate OR 2.58 [1.39–4.81], p value 0.003) (Table 2).
On the other hand, obesity was associated with lower
odds of a single endometriosis diagnosis compared
to non-endometriosis controls (both p values < 0.001)(Tables 1 and 2). In both the self-reported and surgicallyconfirmed recurrence analyses, increased blood pressure
was significant when recurrence was compared to a single diagnosis (univariate analysis) (Tables 1 and 2). In particular, higher systolic blood pressure (130–139 mmHg
group) was associated with recurrent disease compared
to a single endometriosis diagnosis (Tables 1 and 2) (pvalue 0.006 and p value 0.045, respectively). Overall, age
was significantly related to disease recurrence; thosewith recurrent disease were older compared to nonendometriosis controls and those with a single diagnosis (Tables 1 and 2). In particular, in the self-reported
endometriosis recurrence analysis, the recurrence group
had increased odds of being in the older age group(35 + years) versus controls (p value < 0.001) and a single
diagnosis (p value < 0.001) (Table 1). The same was true inthe surgically confirmed group, with the 35 + age group
significantly positively associated with recurrence whencompared to non-endometriosis controls (p value 0.006)(Table 2).
Predicting if endometriosis will reoccur

RiskSLIM analyses, resulting in a points-based system
to score the probability that patients will develop recurrent disease, were employed in both study groups. In the
self-reported (Fig. 2a) and surgically confirmed analyses(See figure on next page.)
Fig. 2 RiskSLIM scores to assess predicted risk of recurrent endometriosis in the self-reported endometriosis analysis group. a Tally of points
and resulting scores for the various combinations of present features in the recurrent endometriosis versus single diagnosis of endometriosis
comparison. Variables were selected to maximise the 5 cross-validation (CV) test AUC. The final score can sit between −2 and 3, with a predicted riskof recurrence at 4.7% for a score of −2 and 88.1% for a high score of 3. d Points and scores for the recurrent endometriosis versus non-endometriosis
control comparison. The final score can also sit between −2 and 3, with a predicted risk of recurrence at 11.9% for a score of −2 and 95.3%
for a high score of 3. b and e Calibration reliability graphs with observed risk (y-axis) and predicated risk (x-axis). The final model is shown in black(with risk scores in black circles), and the 5-CV models on test data shown in grey. The 45° dashed grey line represents a perfect risk calibration.
c and f Receiver operating characteristic (ROC) curve with true positive rate (y-axis) and false positive rate (x-axis). The final model is shownin black and the 5-CV models on test data shown in grey. Area under the ROC curve (AUC) for the 5-CV test and the final model are illustrated
on the bottom right of the ROC curve diagram

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 23 of 35

Fig. 2 (See legend on previous page.)(Fig. 3a), adhesions were the one common variable that
increased the prediction risk score in the models whencomparing recurrent endometriosis to a single endometriosis diagnosis. When applying RiskSLIM to thenon-endometriosis controls and recurrent endometriosis groups, adenomyosis was the common variable that
increased the risk score in both groups, while higher gravidity (3 +) reduced the overall risk score in both groups

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320(Figs. 2d and 3d). Using Fig. 3d as an example, adenomyosis (2 points), plus adhesions (2 points), plus age (35 +)(1 point), plus attendance at an ER (1 point) equals thehighest possible RiskSLIM score of 6, which contributes
to a 98.2% predicted risk for endometriosis recurrence(Fig. 3d, e). As demonstrated in Fig. 3f, this RiskSLIM
model gave the highest AUC: a 5-CV AUC of 0.751. The
more important outcome here is the prediction of recurrent disease compared to a single diagnosis, thus whenusing Fig. 3a as an example, adenomyosis (2 points), plus
diastolic blood pressure (90 + mmHg) (1 point), plus
uterine fibroids (1 point), plus adhesions (1 point) equals
the highest possible RiskSLIM score of 5 for this model,
which contributes to a 95.3% predicted risk for endometriosis recurrence (Fig. 3a, b). However, here we saw
increased overall variability and low AUCs (5-CV AUC of
0.617, Fig. 3c and 5-CV AUC of 0.668, Fig. 2c). Unfortunately, the current models are not able to accurately discriminate for recurrent disease.
Using dates of surgery, we were able to conduct a survival analysis on the surgically confirmed endometriosis
group, allowing us to predict the probability of no disease
recurrence. Self-reported previous diagnosis of endometriosis was a highly significant predictor of disease
recurrence (univariate HR 32.46 [17.69–59.59], adj. p
value < 0.001) (Table 4). For those who self-report a previous diagnosis, the 2- and 5-year probability of no recurrence was 38% and 3%, respectively, compared to 97%
and 90% chance of no recurrence for those who did notreport a previous diagnosis (Table 4 and Fig. 4a). Due toits strength, the feature ‘previous diagnosis of endometriosis’ was not included in the multivariate Lasso model.
Several features were found to be significant in the survival analysis, but only 3 features demonstrated robust
non-zero Lasso coefficients: bowel lesions (1.039), adhesions (0.570) and adenomyosis (0.350) (Table 4). The presence of lesions on the bowel was highly discriminatory
and increased the risk for recurrent disease (univariate
HR 6.25 [3.54–11.03], adj. p value < 0.001) (Table 4 andFig. 4a). At 2 years following their first diagnostic surgery,patients with bowel lesions have a 67% probability of no

Page 24 of 35

recurrence compared to a much higher 96% probabilityof no recurrence in those without bowel lesions (Table 4
and Fig. 4a). At 5 years, the probability of no recurrence
drops to 48% in patients with bowel lesions versus 86% in
those without bowel lesions. The presence of adhesions
visualised at the time of diagnosis was similarly highly
predictive of recurrent disease. Adhesions increased theodds of recurrence (univariate HR 5.49 [2.80–10.76], adj.
p value < 0.001) (Table 4 and Fig. 4c). Two years following
diagnostic surgery, patients with adhesions have an 84%
probability of no recurrence compared to 97% probabilityof no recurrence in those without adhesions (Table 4 andFig. 4c). At 5 years, the probability of no recurrence drops
to 63% in patients with adhesions versus a still relatively
high 92% in those without adhesions. Reporting adenomyosis at the time of surgery was also predictive of disease recurrence (univariate HR 3.28 [1.47–7.32], adj. p
value 0.031), and by 5 years, the probability of no recurrence in those with adenomyosis was 60% compared to
81% in those who did not report adenomyosis (Table 4
and Fig. 4b).

Discussion
The aetiology of recurrent endometriosis is poorly understood, which is problematic since disease recurrence
impacts more than 60% of patients (reviewed by 1, 2).
Here, we identify risk factors for endometriosis recurrence using clinical and survey information from cases
and non-endometriosis controls. Multiple factors wereidentified that increase the risk of developing recurrent
disease; however, 3 key features—adenomyosis, bowel
lesions and adhesions—were repeatedly associated withendometriosis recurrence. The findings of this study may
be helpful for the clinical management of endometriosis
and reducing rates and burden of recurrence.
Presence of self-reported adenomyosis was repeatedly associated with recurrent endometriosis. Adenomyosis also contributed to an increased risk score forpredicting recurrence and significantly increased probability of recurrence 2 and 5 years following an endometriosis diagnosis. Non-invasive diagnostic tests(See figure on next page.)
Fig. 3 RiskSLIM scores to assess predicted risk of recurrent endometriosis in the surgically confirmed analysis group. a Tally of points and resultingscores for the various combinations of present features in the recurrent endometriosis versus single diagnosis of endometriosis comparison.
Variables were selected to maximise the 5 cross-validation (CV) test AUC. The final score sat between −1 and 5, with a predicted risk of recurrence
at 4.7% for a score of −1 and 95.3% for a high score of 5. d Points and scores for the recurrent endometriosis versus non-endometriosis control
comparison. The final score sat between −2 and 6, with a predicted risk of recurrence at 1.8% for a score of −2 and 98.2% for a high score of 6. band e Calibration reliability graphs with observed risk (y-axis) and predicated risk (x-axis). The final model is shown in black (with risk scores in black
circles), and the 5-CV models on test data shown in grey. The 45° dashed grey line represents a perfect risk calibration. c and f Receiver operating
characteristic (ROC) curve with true positive rate (y-axis) and false positive rate (x-axis). The final model is shown in black and the 5-CV models
on test data shown in grey. Area under the ROC curve (AUC) for the 5-CV test and the final model are illustrated on the bottom right of the ROC
curve diagram

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 25 of 35

Fig. 3 (See legend on previous page.)for adenomyosis are improving, with imaging procedures including transvaginal ultrasound and magnetic
resonance imaging (MRI) accurately reflecting histological findings [21, 22]. Using our clinically derived

ultrasound data, we observed an increased risk ofrecurrence relative to non-endometriosis controls forpresence of adenomyosis, as well as increased uterine
volume. We have previously reported that ultrasoundHoldsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 26 of 35

Table 4 Cox proportional hazards regression and 2-year and 5-year probabilities from Kaplan-Meier estimations
Factorn

Univariate survival analysis

Multivariate

Overall survival
HR (95% CI)

p value

Adj. p value

0.014

0.067

Probability of norecurrence at 2 years

Probability of norecurrence at 5 years

Kaplan–Meier p
value

0.049

Lasso coef

Age (years)
Overall

335

1.05 (1.01–1.09)

18–24

84

–

0.97 (0.94–1.00)

0.86 (0.78–0.96)

25–29

107

1.34 (0.55–3.29)

0.519

0.666

0.94 (0.89–0.99)

0.84 (0.75–0.93)

0.000

30–34

67

2.34 (0.96–5.73)

0.062

0.209

0.85 (0.77–0.95)

0.77 (0.66–0.90)

0.000

35 +

77

2.75 (1.18–6.44)

0.019

0.083

0.87 (0.79–0.96)

0.69 (0.57–0.85)

0.000

0.91 (0.86–0.95)

0.82 (0.76–0.89)

0.511

0.666

0.93 (0.89–0.98)

0.77 (0.69–0.87)

0.91 (0.88–0.95)

0.79 (0.73–0.86)

0.597

0.736

0.93 (0.87–0.99)

0.82 (0.72–0.93)

0.93 (0.89–0.98)

0.77 (0.69–0.87)

0.91 (0.86–0.95)

0.82 (0.76–0.89)

Past smokera
No

206

–

Yes

129

1.21 (0.69–2.14)

0.510

0.000

0.600

0.000

0.510

0.000

Current smokera
No

258

–

Yes

77

0.83 (0.41–1.66)

Never smokeda
No

129

–

Yes

206

0.83 (0.47–1.46)

0.511

0.666

0.165

0.343

Age of menarche (years)
Overall334

0.88 (0.74–1.05)

Under 1266–

0.90 (0.83–0.98)

0.76 (0.63–0.90)

12–14

217

0.90 (0.46–1.78)

0.760

0.836

0.91 (0.87–0.95)

0.79 (0.73–0.86)

0.000

15+

51

0.36 (0.10–1.29)

0.118

0.266

0.95 (0.89–1.00)

0.89 (0.75–1.00)

0.000

0.206

0.387

0.250

Graviditya
Overall334

1.19 (0.91–1.57)

0

242

–

0.92 (0.89–0.96)

0.82 (0.76–0.88)

1–2

80

1.11 (0.57–2.16)

0.758

0.836

0.93 (0.86–0.99)

0.78 (0.68–0.90)

0.000

3+

12

2.89 (1.02–8.16)

0.046

0.170

0.67 (0.43–1.00)

0.56 (0.32–1.00)

0.000

0.087

0.237

0.110

Paritya
Overall334

1.35 (0.96–1.89)

0

291

–

0.93 (0.90–0.96)

0.82 (0.77–0.88)

1–2

38

2.01 (0.97–4.18)

0.060

0.209

0.84 (0.72–0.98)

0.67 (0.50–0.88)

0.000

3+

5

3.28 (0.79–13.63)

0.102

0.245

0.75 (0.43–1.00)

0.50 (0.19–1.00)

0.000

0.753

0.836

0.048

Systolic blood pressure (mmHg)
Overall334

1.00 (0.97–1.02)

Under 120220–0.90 (0.85–0.94)

0.79 (0.73–0.86)

120–12978

0.73 (0.35–1.52)

0.393

0.593

0.94 (0.89–1.00)

0.84 (0.75–0.94)

0.000

130–13921

0.52 (0.12–2.17)

0.370

0.593

0.95 (0.86–1.00)

0.86 (0.70–1.00)

0.000

140+

15

0.97 (0.30–3.17)

0.960

0.960

1.00 (1.00–1.00)

0.75 (0.50–1.00)

0.000

0.797

0.864

0.700

Diastolic blood pressure (mmHg)
Overall334

1.00 (0.97–1.03)

Under 80250–

0.91 (0.88–0.95)

0.79 (0.73–0.86)

80–84

47

0.39 (0.12–1.26)

0.116

0.266

0.95 (0.88–1.00)

0.91 (0.83–1.00)

0.000

85–89

16

0.49 (0.07–3.55)

0.477

0.644

0.93 (0.80–1.00)

0.93 (0.80–1.00)

0.000

9+

21

1.66 (0.70–3.94)

0.250

0.437

0.85 (0.71–1.00)

0.66 (0.45–0.98)

0.000

0.178

0.351

0.160

BMI (kg/m2)
Overall

335

1.03 (0.99–1.08)

Normal (18.5–24.9)

194–

0.95 (0.91–0.98)

0.82 (0.76–0.90)

Underweight (< 18.5)

19

2.47 (0.93–6.52)

0.069

0.212

0.78 (0.61–1.00)

0.70 (0.51–0.97)

0.000Pre-obese (25–29.9)

75

1.05 (0.48–2.29)

0.898

0.922

0.90 (0.83–0.97)

0.85 (0.76–0.95)

0.000

Obese (≥ 30)

47

2.75 (1.36–5.57)

0.005

0.034

0.88 (0.78–0.98)

0.65 (0.50–0.85)

0.000

0.011

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 27 of 35

Table 4 (continued)
Factorn

Univariate survival analysis

Multivariate

Overall survival
HR (95% CI)

Probability of norecurrence at 2 years

Probability of norecurrence at 5 years

Kaplan–Meier pvalue

Lasso coef

0.470

0.000

0.640

0.000

0.850

0.000

0.300

0.000

0.062

0.000

0.460

0.000

0.600

0.000

0.039

0.000

0.450

0.000

0.002

0.350

p value

Adj. p value

0.88 (0.74–1.00)

0.88 (0.74–1.00)

0.476

0.644

0.92 (0.89–0.95)

0.79 (0.74–0.85)

0.89 (0.82–0.97)

0.83 (0.74–0.94)

0.642

0.772

0.92 (0.89–0.96)

0.79 (0.73–0.86)

0.90 (0.84–0.97)

0.83 (0.74–0.93)

0.855

0.901

0.92 (0.89–0.96)

0.79 (0.73–0.86)

0.94 (0.90–0.97)

0.82 (0.75–0.89)

0.307

0.507

0.88 (0.82–0.95)

0.77 (0.69–0.87)

0.91 (0.87–0.95)

0.76 (0.69–0.84)

0.066

0.212

0.93 (0.88–0.98)

0.87 (0.80–0.94)

0.92 (0.88–0.97)

0.82 (0.75–0.89)

0.460

0.644

0.91 (0.86–0.96)

0.78 (0.70–0.86)

0.92 (0.89–0.95)

0.80 (0.75–0.86)

0.602

0.736

0.86 (0.69–1.00)

0.75 (0.53–1.00)

0.92 (0.89–0.95)

0.80 (0.75–0.86)

0.046

0.170

0.81 (0.64–1.00)

0.71 (0.50–1.00)

0.92 (0.88–0.95)

0.81 (0.76–0.87)

0.447

0.639

0.91 (0.83–0.99)

0.75 (0.62–0.91)

0.93 (0.90–0.96)

0.81 (0.76–0.87)

0.67 (0.48–0.92)

0.60 (0.41–0.88)

0.88 (0.73–1.00)

0.79 (0.60–1.00)

Severe menstrual paina
No

22

–

Yes

313

1.67 (0.41–6.90)

Severe pelvic pain (non-menstrual)a
No

72

–

Yes

263

1.18 (0.59–2.37)

Dyspareuniaa
No

91

–

Yes

244

0.94 (0.50–1.78)

Attendance at an emergency room for menstrual/pelvic paina
No

204

–

Yes

131

1.35 (0.76–2.38)

Currently taking hormone medicationa
No

216

–

Yes

119

0.54 (0.28–1.04)

Ovarian cystsa
No

175

–

Yes

160

1.24 (0.70–2.19)

Fibrocystic breastsa
No

319

–

Yes

16

1.36 (0.42–4.39)

Uterine fibroidsa
No

318

–

Yes

17

2.57 (1.02–6.49)

Polycystic ovary diseasea
No

274

–

Yes

61

1.31 (0.65–2.64)

Adenomyosisa
No

315

–

Yes

20

3.28 (1.47–7.32)

0.004

0.031

Overall

141

1.01 (1.00–1.02)

0.001

0.008

Under 40 ml

17

US—uterine volume (ml)40–110 ml

107> 110 ml17–~
0.90 (0.84–0.96)

0.68 (0.58–0.80)

0.61 (0.41–0.92)

0.34 (0.13–0.89)
–

0.027

US—log uterine volume (ml)Overall

141

7.72 (1.53–39.07)

0.013

0.067

–

~

US—fibroids present
No

130

–

0.87 (0.81–0.93)

0.70 (0.61–0.81)

Yes

21

1.62 (0.74–3.55)

0.231

0.413

0.85 (0.71–1.00)

0.57 (0.37–0.90)

0.90 (0.84–0.96)

0.70 (0.59–0.83)

1.30 (0.67–2.53)

0.434

0.639

0.82 (0.71–0.93)

0.63 (0.49–0.82)

0.85 (0.79–0.92)

0.66 (0.57–0.77)

0.171

0.347

1.00 (1.00–1.00)

0.85 (0.67–1.00)

0.88 (0.83–0.95)

0.71 (0.62–0.82)

0.072

0.213

0.82 (0.70–0.96)

0.55 (0.38–0.82)

0.230

~

0.430

~

0.150

~

0.068

~

US—ovarian cysts present
No

98

Yes

53

US—polycystic ovaries present
No

134

–

Yes

17

0.37 (0.09–1.54)

US—adenomyosis present
No

115

–

Yes

36

1.90 (0.94–3.81)

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 28 of 35

Table 4 (continued)
Factorn

Univariate survival analysis

Multivariate

Overall survival
HR (95% CI)

Probability of norecurrence at 2 years

Probability of norecurrence at 5 years

Kaplan–Meier pvalue

Lasso coef

0.700

~

0.003

~

0.093

~

0.960

0.000

0.260

0.000

0.840

0.000

0.023

0.000

0.310

0.000

0.089

0.000

< 0.001

~

0.380

0.000

< 0.001

~

0.150

~

0.001

~

p value

Adj. p value

0.86 (0.80–0.93)

0.69 (0.60–0.80)

0.705

0.822

0.93 (0.82–1.00)

0.61 (0.40–0.95)

0.88 (0.82–0.93)

0.71 (0.62–0.81)

0.006

0.038

0.80 (0.59–1.00)

0.00 (NA–NA)

0.89 (0.83–0.94)

0.69 (0.60–0.79)

0.102

0.245

0.72 (0.52–1.00)

0.72 (0.52–1.00)

0.92 (0.88–0.95)

0.80 (0.75–0.86)

0.955

0.960

0.93 (0.82–1.00)

0.79 (0.61–1.00)

0.92 (0.89–0.95)

0.81 (0.76–0.87)

0.260

0.444

0.89 (0.79–1.00)

0.69 (0.52–0.91)

0.93 (0.89–0.96)

0.79 (0.73–0.86)

0.845

0.901

0.88 (0.81–0.96)

0.81 (0.72–0.93)

0.92 (0.89–0.96)

0.82 (0.77–0.87)

0.027

0.110

0.82 (0.67–1.00)

0.62 (0.44–0.87)

0.93 (0.90–0.97)

0.81 (0.74–0.89)

0.310

0.507

0.89 (0.83–0.95)

0.78 (0.70–0.87)

0.91 (0.87–0.95)

0.77 (0.70–0.84)

0.094

0.242

0.93 (0.88–0.99)

0.87 (0.80–0.95)

0.97 (0.96–0.99)

0.90 (0.86–0.95)

0.000< 0.001

0.38 (0.24–0.60)

0.03 (0.01–0.24)

0.91 (0.87–0.95)

0.78 (0.72–0.85)

0.386

0.593

0.94 (0.88–0.99)

0.84 (0.75–0.94)

0.90 (0.85–0.96)

0.73 (0.64–0.83)

0.000< 0.0010.55 (0.34–0.90)

0.24 (0.08–0.73)

0.91 (0.85–0.97)

0.71 (0.61–0.83)

0.154

0.330

0.78 (0.66–0.92)

0.59 (0.44–0.80)

0.89 (0.84–0.95)

0.71 (0.62–0.82)

0.67 (0.47–0.95)

0.44 (0.25–0.80)

US—adenomyosis linear striations present
No

135

–

Yes

16

1.20 (0.47–3.09)

US—adenomyosis heterogeneous myometrium
No

141

–

Yes

10

3.92 (1.48–10.38)

US—adenomyosis thickened posterior wall
No

135

–

Yes

16

2.23 (0.85–5.83)

Pre-cancer of the cervix or an abnormal Papanicolaou testa
No

319

–

Yes

16

1.03 (0.32–3.33)

Cervical intraepithelial neoplasia (CIN) (pathology)
No

298

–

Yes

37

1.55 (0.72–3.31)

Food allergies or intolerancesa
No

258

–

Yes

77

0.93 (0.48–1.83)

Disturbance to taste or smella
No

312

–

Yes

23

2.36 (1.10–5.04)

Hay fevera
No

206

–

Yes

129

1.34 (0.76–2.36)

Eczemaa
No

236

–

Yes

99

0.55 (0.27–1.11)

Previous diagnosis of endometriosisa
No

306

–

Yes

29

32.46 (17.69–59.59)

Family history of endometriosisa
No

252

–

Yes

82

0.73 (0.37–1.48)

US—endometriosis present (excluding OMA)
No

137

–

Yes

14

6.26 (2.99–13.09)

US—endometrioma
No

107

–

Yes

44

1.63 (0.83–3.18)

US—adhesions
No

136

–

Yes

15

3.32 (1.56–7.05)

0.002

0.018

335

1.02 (1.01–1.02)

0.000< 0.001

rASRM score
Overall

0.000Stage of endometriosis (rASRM)
Stage 1

192–

0.97 (0.94–1.00)

0.91 (0.86–0.96)

Stage 253

3.40 (1.47–7.88)

0.004

0.033

0.89 (0.80–0.99)

0.71 (0.56–0.89)< 0.001
0.000

Stage 337

3.44 (1.35–8.76)

0.010

0.057

0.91 (0.82–1.00)

0.64 (0.44–0.94)

0.000Stage 453

6.79 (3.29–14.00)

0.000< 0.0010.76 (0.65–0.89)

0.59 (0.46–0.77)

0.000Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 29 of 35

Table 4 (continued)
Factorn

Univariate survival analysis

Multivariate

Overall survival
HR (95% CI)

Probability of norecurrence at 2 years

Probability of norecurrence at 5 years

Kaplan–Meier pvalue

Lasso coef

< 0.001

0.570

0.140

0.000

0.013

0.000

0.009

0.000

< 0.001

0.000

0.390

0.000

0.210

0.000

0.042

0.000

< 0.001

1.039

0.700

0.000

0.550

0.000

0.450

0.000

0.750

0.000

0.086

0.000

p value

Adj. p value

0.97 (0.95–1.00)

0.92 (0.88–0.97)

0.000< 0.001

0.84 (0.77–0.90)

0.63 (0.54–0.74)

0.92 (0.89–0.96)

0.82 (0.76–0.87)

0.143

0.315

0.88 (0.78–0.98)

0.69 (0.52–0.91)

0.93 (0.90–0.96)

0.84 (0.78–0.90)

0.015

0.067

0.88 (0.81–0.96)

0.68 (0.56–0.83)

0.84 (0.74–0.96)

0.67 (0.54–0.84)

0.011

0.060

0.93 (0.90–0.96)

0.82 (0.77–0.88)

0.97 (0.95–1.00)

0.84 (0.78–0.91)

0.000

0.002

0.79 (0.72–0.88)

0.71 (0.62–0.82)

0.94 (0.89–0.98)

0.82 (0.74–0.91)

0.389

0.593

0.90 (0.86–0.95)

0.79 (0.72–0.86)

0.92 (0.89–0.96)

0.82 (0.76–0.88)

0.214

0.393

0.89 (0.83–0.97)

0.75 (0.64–0.87)

0.92 (0.89–0.95)

0.80 (0.75–0.86)

0.075

0.213

0.50 (0.13–1.00)

0.50 (0.13–1.00)

0.96 (0.94–0.99)

0.86 (0.81–0.92)

0.000< 0.001

0.67 (0.55–0.82)

0.48 (0.33–0.67)

0.92 (0.89–0.95)

0.80 (0.74–0.85)

0.699

0.822

0.87 (0.72–1.00)

0.87 (0.72–1.00)

0.92 (0.87–0.98)

0.85 (0.77–0.93)

0.546

0.689

0.91 (0.88–0.95)

0.78 (0.72–0.85)

0.91 (0.87–0.94)

0.80 (0.74–0.86)

0.448

0.639

0.97 (0.92–1.00)

0.80 (0.64–1.00)

0.93 (0.89–0.97)

0.79 (0.72–0.87)

0.747

0.836

0.90 (0.86–0.96)

0.82 (0.74–0.90)

0.92 (0.89–0.96)

0.82 (0.76–0.88)

0.089

0.237

0.89 (0.83–0.96)

0.75 (0.64–0.88)

Adhesions (surgical)
No

201

–

Yes

134

5.49 (2.80–10.76)

Superficial ovarian lesion(s)
No

289

–

Yes

46

1.72 (0.83–3.56)

Deep ovarian lesion(s)
No

253

–

Yes

82

2.06 (1.15–3.67)

Superficial peritoneal lesion(s)
No

45

–

Yes

290

0.44 (0.23–0.83)

Deep peritoneal lesion(s)
No

230

–

Yes

105

3.03 (1.72–5.35)

Pouch of Douglas
No

142

–

Yes

193

1.30 (0.71–2.38)

UV pouch
No

246

–

Yes

89

1.46 (0.80–2.67)

Bladder
No

333

–

Yes

2

6.15 (0.83–45.33)

Bowel
No

280

–

Yes

55

6.25 (3.54–11.03)

Tubes
No

324

–

Yes

11

0.76 (0.18–3.12)

Pelvic side wall
No

157

–

Yes

178

1.22 (0.64–2.30)

Pararectal space
No

307

–

Yes

28

0.67 (0.24–1.87)

Uterosacral ligament
No

211

–

Yes

124

0.91 (0.51–1.62)

Other
No

245

–

Yes

90

1.67 (0.92–3.03)~ Data was not included in the multivariate Lasso modelaPatient reported variablediagnosed adenomyosis is associated with stage 4 endometriosis [23]. As the symptoms of adenomyosis commonly mimic endometriosis, it is very probable that
individuals are undergoing reoperation for treatmentof suspected recurrent endometriosis, when in fact
the primary cause of recurring symptoms is adenomyosis. This is a scenario that may have occurred in ourstudy. Others have reported a relationship between

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Page 30 of 35

Fig. 4 Kaplan-Meier curves for the surgically confirmed endometriosis recurrence group. Survival analysis was performed on data from patientswith confirmed endometriosis (in the surgically confirmed analysis group). a Presence of lesions on the bowel, b self-reported diagnosisof adenomyosis and c presence of adhesions. a–c Red = no (variable not present), blue = yes (variable present). Vertical dashed line placed at 2 years
and 5 years (time). Kaplan-Meier p values are included on the graph (bottom left)

adenomyosis of the outer uterine wall and bowel endometriosis [24, 25]. Recently, it has been highlighted that
nodules in the bowel may not be caused by deep-infiltrating endometriosis, but rather the result of posterior
uterine adenomyosis [26]. It is suggested that becauseof the close proximity between posterior wall adenomyosis and the bowel, it could attach to and seed in
the adjacent colon, or vice versa, and increase the likelihood of adhesions obliterating the pouch of Douglas[25].
We found that endometriotic bowel lesions were associated with higher risk of disease recurrence, especiallyin surgically confirmed recurrent patients. Bowel lesions
are present in 3–37% of all endometriosis patients [27]and are more common on the sigmoid colon and rectum [25]. Endometriosis of the bowel may be solitary,
but often presents with ovarian or uterosacral ligamentendometriosis nodules and adenomyosis [24]. In thecontext of the overall findings of our study, it is acknowledged that bowel endometriosis is reported to be associated with advanced pelvic adhesions and fibrosis [25, 28].
Therefore, a picture is emerging where an unfavourable
paradigm of adenomyosis, bowel lesions and adhesions
co-exist to increase the severity of disease and promote
an environment favourable for endometriosis recurrence. There are reports in the literature of patients withbowel endometriosis developing recurrence; however,these are often case reports [29–31] and cannot be accurately compared to recurrence rates of other subtypesof endometriosis (e.g. peritoneal lesions or endometrioma). One systematic review reported surgically confirmed endometriosis recurrence to be 13.9% following

bowel resection [29]. A second systematic review showed
higher recurrence rates (visually and/or histologically
proven recurrence) of 45% following bowel resection
anastomosis and 35% following other surgical methods(shaving, superficial excision, full thickness disc excision) [32]. We did not collect information pertaining to
the type of procedure performed for removal of bowel
disease, therefore cannot speculate if our cohort was different or similar to the report of Meuleman et al. Medical
management of bowel endometriosis can lead to symptom recurrence following discontinuation of therapy, andtherefore, surgical management is considered to be theprimary treatment for symptomatic severe endometriosis
of the bowel [32]. Yet, a histological study of 10 patients
who underwent colorectal resection, with edges ≥ 2 cm
away from the macroscopic nodule limits, identified
microscopic endometriosis in the colorectal muscularis
layer adjacent and distal from the macroscopic nodule
limits [24]. Therefore, it is important to raise the questionof feasibility of complete resection of bowel endometriosis if microscopic implants remain in patients managed
by segmental resection [24].
Notwithstanding, the possibility of microscopic endometriosis remaining following resection or bowel shaving, lesions on the bowel are often not removed or
incompletely removed due to clinical considerations. The
reasons for this vary and may be anecdotal, but operative morbidity may take priority over complete disease
resection [27]. The current definition of recurrent endometriosis specifies ‘lesion recurrence (…) after previous complete excision of the disease’ [7]; this presents
a limitation to many published works as description ofHoldsworth‑Carson et al. BMC Medicine(2024) 22:320

complete/incomplete excision is often not provided.
Therefore, it is difficult to ascertain if studies describing
recurrent endometriosis are actually describing persistent or residual endometriosis instead of de novo disease.
One study quantified the risk of recurrence after complete resection of endometriosis, versus leaving residual
disease and found while total resection did decrease therisk of disease recurrence, it increased the risk of postsurgical complications and was reliant on surgeon expertise [33]. In our study, we took steps to ensure those withincomplete resection or abandoned surgeries were notincluded in the subset of patients classified as having
recurrent disease, and therefore, we can infer that presence of bowel disease at the index surgery is associatedwith de novo lesion recurrence, not due to disease thatwas left behind in previous surgeries.
One consideration that will influence a surgeon’s decision regarding complete removal of endometriosis andincreased likelihood of reoperation is post-surgical adhesions. The risk of adhesions after any abdominopelvic
operation has previously been reported to be between 55
and 100% [34]. Presence of adhesions was significantly
associated with endometriosis disease recurrence in thecurrent study. The observed adhesions in our participants were likely a result of the inflammatory endometriotic lesions themselves or from their previous surgery
or surgeries.
Strategies to reduce adhesion formation following surgery have been the topic of two recent Cochrane reviews
examining the effectiveness of barrier or gel agents,
which report scanty evidence demonstrating effectiveness in adhesion prevention [35] or low-quality evidence
supporting barrier agents in reducing adhesion formation [36]. New data is emerging on novel treatments foradhesions [37, 38], as well as non-invasive methods ofdetecting adhesions, such as computed tomography (CT)imaging [39]. One study showed treatment with intraperitoneal triamcinolone (a glucocorticoid used to treatskin conditions and autoimmune disorders) following
gynaecological surgery reduced adhesions at a repeat
abdominal surgery [38]. With respect to adhesion detection via imaging for diagnosis or as part of pre-surgicalplanning, our data demonstrated that ultrasound was
useful in identifying adhesions in association with disease recurrence. Thus, increased surveillance and imaging should be considered the first-line approach to assess
the presence of adhesions when suspicious of endometriosis recurrence, as opposed to performing multiple surgeries, which may increase the risk of further adhesions
and recurrent disease.
Common biological mechanisms tie adhesions, adenomyosis and bowel lesions together—inflammation, fibrosis and epithelial-to-mesenchymal transition (EMT).

Page 31 of 35

These pathways are ingrained in many of the pathophysiological theories of endometriosis lesion development
and survival and have been extensively reviewed [40–43].
A deeper understanding of these mechanisms, specificto their contribution to disease recurrence, may provide
researchers and clinicals with an opportunity to develop
targeted therapies that could be utilised to prevent disease from returning.
In this study, a positive diagnosis of endometriosis(recurrent disease or first diagnosis) was associated withdecreased likelihood of hormone medication usage compared to non-endometriosis controls. A recent publication reported reduced reoperation for endometriosis inpatients who are treated with hormones before and after
their first endometriosis surgery, with the median time
to reoperation estimated to be 9 years compared to just
3 years in those not taking hormone therapy [44]. However, a 2020 Cochrane Review (of 25 trials) exploring theeffectiveness of hormonal suppression before, after orboth before and after surgery for endometriosis determined that the data was inconclusive, stating that those‘who receive postsurgical medical therapy compared withno medical therapy or placebo may experience benefit interms of (…) disease recurrence (…). There is insufficientevidence regarding hormonal suppression therapy atother time points in relation to surgery for women withendometriosis’ [45]. It is not known why our population
were less likely to report use of hormones, and while it
could be speculated that a proportion were trying toconceive, we cannot report that with certainty. It is clear,
however, that more comprehensive prospective studies
are required to unequivocally answer if hormonal suppression can prevent endometriosis recurrence.
In addition to the characteristics described above,some other factors were found to be associated with anincreased risk of recurrence (and increased risk score)
and arose on more than one occasion. The relationshipbetween endometriosis and reduced gravidity and parity
is well-established [46, 47]. However, in our study, recurrent endometriosis patients had increased odds of higher
gravidity and/or parity compared to those with a single
diagnosis of endometriosis. It is likely this phenomenon
is age-related, with recurrent patients more likely to beolder than those receiving a single diagnosis and therefore, having greater amount of time to achieve morepregnancies. This is supported by our recent study thatfound the likelihood of a new diagnosis of endometriosis in those with pelvic pain, no previous laparoscopy anda normal ultrasound, was lower in women aged 40 andabove [48]. On the other hand, patients of greater age andhigher gravidity and parity may be more likely to accept
reoperation as a treatment and elect for a hysterectomy,

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

as the desire for future fertility has lapsed, thus falling
into the recurrence cohort in this analysis.
A lower BMI has commonly been associated withincreased risk of endometriosis [49–51]. However, following stratification of our endometriosis groups intorecurrent and single diagnoses, we found that obesity
was associated with an increased likelihood of endometriosis recurrence compared to patients with a single
diagnosis of endometriosis (in the surgically confirmed
analysis only). Interestingly, we also found an association
between recurrent endometriosis and increased bloodpressure compared to those with a single diagnosis. Yet,when recurrent endometriosis was compared to nonendometriosis controls, the dynamic shifted and obesity
became protective. In other words, obesity reduced therisk of recurrent endometriosis compared to controls.
The presence of worsening metabolic disease in endometriosis is well established; evidence in the literaturedescribes high blood pressure, hypercholesterolemia,
fasting glucose levels and cardiovascular disease in endometriosis patients over time [52–54]. Critically, there isan established relationship between chronic pain andthe development of hypertension [55, 56], and the risk ofcardiovascular disease [57]. Though this requires further
investigation, we suggest that recurrent endometriosis
may represent a cohort of patients with an increased propensity for the development of cardiometabolic diseases(including obesity and hypertension), and that thesepatients warrant long-term surveillance and monitoringin order to reduce cardiometabolic risk.
Inherently, it is perceived that data from self-reported
surveys are limited, as information can suffer from
response bias or recall bias. However, recent studies havefound that patients who self-report a previous endometriosis diagnosis do so with accuracy [58, 59]. In ourstudy, almost 80% of patients with surgically confirmed
recurrent endometriosis also self-reported a previous
diagnosis, validating that a patient’s account of a positive diagnosis of endometriosis should be considered
reliable, in the absence of any confirmatory medical
documentation.
This study considered the presence of de novo lesions
following index surgery a pre-requisite for categorisation
into the recurrent endometriosis group. Yet, to achieve
this status, it must be kept in mind that multiple likely
events were necessary in the lead up to reoperation. For
example, the individual must have experienced symptom
recurrence following a previous surgery or have beenunresponsive to non-surgical management (i.e. hormonal
treatment) of returning symptoms. However, not all individuals will elect non-surgical management, for example,
if they have had a prior negative experience with the side
effects of hormonal therapies and a positive experience ofPage 32 of 35

symptom relief following surgery. In addition, repeat surgery must be consistent with the patient’s desire as wellas the surgeon’s/hospital’s assessment and practice. Allof these aforementioned decisions are complex and subjective, and further randomised controlled clinical trials(RCTs) are necessary to overcome and better understandthese potential biases.
The strengths of this study include its novelty, size,
comprehensive clinical phenotyping and multivariate analysis. Furthermore, our inclusion of two analytic
groups defining endometriosis recurrence increases therobustness of the findings. However, we acknowledge thefollowing limitation, while the self-reported analysis utilised pathology-confirmed endometriosis in the selection
and allocation of participants, the surgically confirmed
analysis relied on screening of surgical records, therefore surgical visualisation. While the outcomes of thisresearch bring us closer to developing a clinical model
to predict the chance of recurrence for those diagnosed
with endometriosis, the accuracy of these tools are not
yet precise enough to correctly classify disease outcomes.
The prediction model is highly influenced by the samples
on which it was developed (in this case, patients with significant pelvic pain or symptoms of endometriosis thatwarranted surgery in a tertiary hospital), and therefore,
generalising to other populations may be less accurate.
Further external validation in more diverse populations isnecessary. We also expected to observe more replicationof features between our two study analyses, self-reported
and surgically confirmed endometriosis recurrence. We
may have seen improved replication or more accurate
risk prediction if we had further stratified repeat surgeries by procedure type, particularly, the involvement of ahysterectomy (with/without ovarian conservation). Hysterectomy at reoperation is a notable consideration, given
this larger procedure is associated with reduced risk ofrecurrence [2, 60, 61]. We have specifically examined
endometriosis cases (single and recurrent) attributed by
the physical presence of lesions, visualised at surgery, andhave not considered symptom-based suspected recurrence. The mechanisms of symptom only recurrence
versus new lesion formation are likely to have very different aetiologies, and therefore, interpretation of thefindings of this investigation should only be consideredin the context of lesions being present. However, as our
focus was on surgical patients, our study did not include
patients with a clinical diagnosis of recurrence (for example, recurrence found on imaging [ultrasound or MRI] ordiagnostic laparoscopy alone) who were managed nonsurgically. A final limitation of our study is time; it would
have been beneficial to follow participants for a longer
follow-up period to monitor for disease recurrence andthe long-term effectiveness of interventions.

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

Conclusions
A picture has emerged that highlights several features tobe important for better understanding the mechanisms
behind recurrent endometriosis. A negative paradigm
consisting of lesions located on the bowel, post-surgicaladhesions and adenomyosis are observed to increase theseverity of disease and the risk of endometriosis recurrence. This information has been derived from a combination of patient reported measures and clinical records,
highlighting and validating the use of self-reported
patient histories for prior diagnoses of endometriosis.
In the course of diagnosing suspected recurrent disease,the presence of other endometriosis features (lesions on
the bowel, adhesions) and gynaecological comorbidities (adenomyosis) should also be accurately assessed at
the same time [44]. Being able to provide patients morecomprehensive information on the likelihood of their disease returning following complete surgical removal will
empower patients with knowledge and a level of reassurance not previously available. While further work isneeded to validate our tool and its predictive power, thecurrent study provides evidence of clinically detectablerisk factors associated with an increased chance of disease recurrence.
Abbreviations
AUC​	Area under the curve
BMI	Body mass index
BP	Blood pressure
CI	Confidence interval
CIN	Cervical intraepithelial neoplasiacm	Centimetre
CT	Computed tomography
CV	Cross-validation
EMT	Epithelial-to-mesenchymal transition
ER	Emergency roomHR	Hazards ratio
MRI	Magnetic resonance imagingn	Number
NHMRC	National Health and Medical Research Council
OR	Odds ratiorASRM	Revised American Society for Reproductive Medicine
RCT​	Randomised controlled clinical trial
RiskSLIM	Risk-calibrated Supersparse Linear Integer Models
ROC	Receiver operating characteristic
RWH	Royal Women’s Hospital
STROBE	STrengthening the Reporting of OBservational studies in Epidemiology
UV	UterovesicalAcknowledgements
We thank research nurses and research assistants (Royal Women’s Hospital) for
recruiting participants and collecting data. Thank-you to the nurses, surgeons,pathologists, theatre and booking staff at The Royal Women’s Hospital. Mostof all, thank you to the patients who generously agreed to donate their timeand information to this study.
Authors’ contributions
All authors contributed to the conception and design of the research; S.J.H-C,
J.C, D.A.M, R.L, B.K.J, M.J.G, M.C, T.M, D.N, U.P.D, M.H and P.A.W.R were involved indata curation and/or conducted formal analysis; all authors contributed to themethodology and acquisition or interpretation of data for the work; S.J.H-C,
D.N, U.P.D, M.H and P.A.W.R were involved in supervision; S.J.H-C, G.W.M, C.R,
J.F.D, J.E.G, M.H and P.A.W.R acquired data and funding and resources; and all

Page 33 of 35

authors contributed to writing - original draft/review/revise/editing and gave
final approval of the version to be submitted for publication. All authors had
full access to all the data in the study and accept responsibility to submit for
publication. All authors are accountable for all aspects of the works accuracy
or integrity.
Authors’ Twitter handles
Twitter handles: @carsonsarahj, @DrJaneGirling, @DonoghueJacqui, @meaghan_griff.
Funding
This work was partially supported by National Health and Medical ResearchCouncil (NHMRC) Grants GNT1105321 and GNT1012245 (P.A.W.R., G.W.M.,
J.E.G., S.J.H-C.), GNT1026033 (G.W.M.) and NHMRC Medical Research Future
Fund GNT1199715 (P.A.W.R., M.H., S.J.H-C. and J.F.D.). G.W.M. was supported by
NHMRC Fellowships GNT1078399 and GNT1177194.
Availability of data and materials
Individual participant data (including data dictionaries) are not available forsharing. The ethics approvals of this study prohibit the study team from mak‑ing the dataset publicly available.

Declarations
Ethics approval and consent to participate
All participants provided written consent and the study was approved by theRoyal Women’s Hospital Human Research Ethics Committee (Project #10-43,#11-24 and #16-43).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Author details
1
Department of Obstetrics, Gynaecology and Newborn Health, Universityof Melbourne and Gynaecology Research Centre, Royal Women’s Hospital,
Grattan St & Flemington Rd, Parkville, VIC 3052, Australia. 2 The Julia Argyrou
Endometriosis Centre, Epworth HealthCare, Ground Floor, 185‑187 Hoddle
Street, Richmond, VIC 3121, Australia. 3 Melbourne Bioinformatics, Universityof Melbourne, 21 Bedford St, North Melbourne, VIC 3051, Australia. 4 The
Kirby Institute, University of New South Wales, High Street, Kensington, NSW
2052, Australia. 5 Centre for Women’s Infectious Diseases, The Royal Women’s
Hospital, Grattan St & Flemington Rd, Parkville, VIC 3052, Australia. 6 UltrasoundServices, Royal Women’s Hospital, Grattan St & Flemington Rd, Parkville, VIC
3052, Australia. 7 Department of Radiology, University of Melbourne, Royal Mel‑bourne Hospital, Royal Parade, Parkville, VIC 3050, Australia. 8 Faculty of Medi‑cine, Department of Obstetrics and Gynaecology, Hadassah Medical Center,
P.O Box 12000, Jerusalem 91120, Israel. 9 Institute for Molecular Bioscience,
University of Queensland, 306 Carmody Road, St Lucia, Brisbane, QLD 4072,
Australia. 10 Department of Anatomy, School of Biomedical Sciences, Universityof Otago, 270 Great King Street, Dunedin 9016, New Zealand.
Received: 5 March 2024 Accepted: 1 July 2024

References
1. Selçuk I, Bozdağ G. Recurrence of endometriosis; risk factors, mecha‑
nisms and biomarkers; review of the literature. J Turk Ger Gynecol Assoc.
2013;14(2):98–103.
2. Guo SW. Recurrence of endometriosis and its control. Hum Reprod
Update. 2009;15(4):441–61.
3. Busacca M, Chiaffarino F, Candiani M, Vignali M, Bertulessi C, Oggioni
G, et al. Determinants of long-term clinically detected recurrence rates
of deep, ovarian, and pelvic endometriosis. Am J Obstet Gynecol.
2006;195(2):426–32.

Holdsworth‑Carson et al. BMC Medicine

4.
5.
6.
7.
8.

9.

10.
11.
12.
13.

14.
15.

16.
17.
18.
19.
20.
21.

22.
23.

24.

25.
26.

(2024) 22:320

Tandoi I, Somigliana E, Riparini J, Ronzoni S, Vigano P, Candiani M. Highrate of endometriosis recurrence in young women. J Pediatr Adolesc
Gynecol. 2011;24(6):376–9.
Horne AW, Saunders PTK, Abokhrais IM, Hogg L. Top ten endometriosis
research priorities in the UK and Ireland. Lancet. 2017;389(10085):2191–2.
Group TmotEGC, Becker CM, Bokor A, Heikinheimo O, Horne A,
Jansen F, et al. ESHRE guideline: endometriosis. Hum Reprod Open.
2022;2022(2):hoac009.
International Working Group of Aagl EE, Wes, Tomassetti C, Johnson NP,
Petrozza J, Abrao MS, et al. An international terminology for endometrio‑
sis. Hum Reprod Open. 2021;2021(4):hoab029-hoab.
Zakhari A, Delpero E, McKeown S, Tomlinson G, Bougie O, Murji A.
Endometriosis recurrence following post-operative hormonal sup‑pression: a systematic review and meta-analysis. Hum Reprod Update.
2021;27(1):96–107.
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke
JP. The Strengthening the Reporting of Observational Studies in Epidemi‑
ology (STROBE) statement: guidelines for reporting observational studies.
Lancet. 2007;370(9596):1453–7.
Canis M, Donnez JG, Guzick DS, Halme JK, Rock JA, Schenken RS, et al.
Revised american society for reproductive medicine classification ofendometriosis: 1996. Fertil Steril. 1997;67(5):817–21.
O’Malley J, Iacovou M, Holdsworth-Carson SJ. Evidence for an association
between endometriosis and allergic and non-allergic food hypersensitiv‑
ity is lacking. Front Reprod Health. 2021;3:726598.
Bungum HF, Vestergaard C, Knudsen UB. Endometriosis and type 1 aller‑
gies/immediate type hypersensitivity: a systematic review. Eur J Obstet
Gynecol Reprod Biol. 2014;179:209–15.
Shafrir AL, Palmor MC, Fourquet J, DiVasta AD, Farland LV, Vitonis AF,
et al. Co-occurrence of immune-mediated conditions and endome‑
triosis among adolescents and adult women. Am J Reprod Immunol.
2021;86(1):e13404.
R Core Team. R: a language and environment for statistical computing.
Vienna: R Foundation for Statistical Computing; 2022. Available from:https://​www.R-​proje​ct.​org/.
Lee TF, Chao PJ, Ting HM, Chang L, Huang YJ, Wu JM, et al. Using multivari‑ate regression model with least absolute shrinkage and selection opera‑
tor (LASSO) to predict the incidence of xerostomia after intensity-modu‑
lated radiotherapy for head and neck cancer. PLoS One. 2014;9(2):e89700.
Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized
linear models via coordinate descent. J Stat Softw. 2010;33(1):1–22.
Ustun B, Rudin C. Learning optimized risk scores. J Mach Learn Res.
2019;20:1–75.
Struck AF, Ustun B, Ruiz AR, Lee JW, LaRoche SM, Hirsch LJ, et al. Associa‑
tion of an electroencephalography-based risk score with seizure prob‑
ability in hospitalized patients. JAMA Neurol. 2017;74(12):1419–24.
Therneau TM, Grambsch PM. Modeling survival data: extending the Coxmodel. New York: Springer; 2000.
Alboukadel K, Marcin K, Przemyslaw B. survminer: drawing survival curves
using ‘ggplot2’. R package version 0.4.9. 2021. Available from: https://​CRAN.R-​proje​ct.​org/​packa​ge=​survm​iner.
Champaneria R, Abedin P, Daniels J, Balogun M, Khan KS. Ultrasoundscan and magnetic resonance imaging for the diagnosis of adenomyosis:
systematic review comparing test accuracy. Acta Obstet Gynecol Scand.
2010;89(11):1374–84.
Gordts S, Grimbizis G, Campo R. Symptoms and classification of uterine
adenomyosis, including the place of hysteroscopy in diagnosis. Fertil
Steril. 2018;109(3):380-8.e1.
Dior UP, Nisbet D, Fung JN, Foster G, Healey M, Montgomery GW, et al.
The association of sonographic evidence of adenomyosis with severe
endometriosis and gene expression in eutopic endometrium. J Minim
Invasive Gynecol. 2019;26(5):941–8.
Badescu A, Roman H, Barsan I, Soldea V, Nastasia S, Aziz M, et al. Patternsof bowel invisible microscopic endometriosis reveal the goal of surgery:removal of visual lesions only. J Minim Invasive Gynecol. 2018;25(3):522-7.
e9.
Yong PJ, Bedaiwy MA, Alotaibi F, Anglesio MS. Pathogenesis of bowel
endometriosis. Best Pract Res Clin Obstet Gynaecol. 2021;71:2–13.
Donnez J, Stratopoulou CA, Marie-Madeleine D. Endometriosis andadenomyosis: similarities and differences. Best Pract Res Clin Obstet
Gynaecol. 2023;92:102432.

Page 34 of 35

27. Wolthuis AM, Meuleman C, Tomassetti C, D’Hooghe T, de Buck van
Overstraeten A, D’Hoore A. Bowel endometriosis: colorectal surgeon’s
perspective in a multidisciplinary surgical team. World J Gastroenterol.
2014;20(42):15616–23.
28. Kondo H, Hirano Y, Ishii T, Hara K, Obara N, Wang L, et al. Intestinal endo‑
metriosis treated by laparoscopic surgery: case series of 5 patients. Surg
Case Rep. 2020;6(1):49.
29. De Cicco C, Corona R, Schonman R, Mailova K, Ussia A, Koninckx P.
Bowel resection for deep endometriosis: a systematic review. BJOG.
2011;118(3):285–91.
30. Yela DA, Vitale SG, Vizotto MP, Benetti-Pinto CL. Risk factors for recur‑
rence of deep infiltrating endometriosis after surgical treatment. J Obstet
Gynaecol Res. 2021;47(8):2713–9.
31. Hernández Gutiérrez A, Spagnolo E, Zapardiel I, Garcia-Abadillo Seivane R,
López Carrasco A, Salas Bolívar P, et al. Post-operative complications andrecurrence rate after treatment of bowel endometriosis: comparison of
three techniques. Eur J Obstet Gynecol Reprod Biol X. 2019;4:100083.
32. Meuleman C, Tomassetti C, D’Hoore A, Van Cleynenbreugel B, Penninckx
F, Vergote I, et al. Surgical treatment of deeply infiltrating endometriosis
with colorectal involvement. Hum Reprod Update. 2011;17(3):311–26.
33. Cao Q, Lu F, Feng WW, Ding JX, Hua KQ. Comparison of complete andincomplete excision of deep infiltrating endometriosis. Int J Clin Exp Med.
2015;8(11):21497–506.
34. Herrmann A, De Wilde RL. Adhesions are the major cause of complica‑
tions in operative gynecology. Best Pract Res Clin Obstet Gynaecol.
2016;35:71–83.
35. Ahmad G, Thompson M, Kim K, Agarwal P, Mackie FL, Dias S, et al. Fluid
and pharmacological agents for adhesion prevention after gynaecologi‑
cal surgery. Cochrane Database Syst Rev. 2020;7(7):Cd001298.
36. Ahmad G, O’Flynn H, Hindocha A, Watson A. Barrier agents for adhesion
prevention after gynaecological surgery. Cochrane Database Syst Rev.
2015;2015(4):Cd000475.
37. Yang L, Li Z, Chen Y, Chen F, Sun H, Zhao M, et al. Elucidating the novel
mechanism of ligustrazine in preventing postoperative peritoneal adhe‑sion formation. Oxid Med Cell Longev. 2022;2022:9226022.
38. Purandare N, Kramer KJ, Minchella P, Ottum S, Walker C, Rausch J, et al.
Intraperitoneal triamcinolone reduces postoperative adhesions, possibly
through alteration of mitochondrial function. J Clin Med. 2022;11(2):301.
39. Gopireddy DR, Soule E, Arif-Tiwari H, Sharma S, Kanmaniraja D, Jain
K, et al. Spectrum of CT findings related to bowel adhesions withoutbowel obstruction: a comprehensive imaging review. J Clin Imaging Sci.
2020;10:80.
40. Garcia Garcia JM, Vannuzzi V, Donati C, Bernacchioni C, Bruni P, Petraglia
F. Endometriosis: cellular and molecular mechanisms leading to fibrosis.
Reprod Sci. 2023;30(5):1453–61.
41. Saunders PTK, Horne AW. Endometriosis: etiology, pathobiology, andtherapeutic prospects. Cell. 2021;184(11):2807–24.
42. Konrad L, Dietze R, Riaz MA, Scheiner-Bobis G, Behnke J, Horné F, et al.
Epithelial-mesenchymal transition in endometriosis-when does it hap‑pen? J Clin Med. 2020;9(6):1915.
43. Hogg C, Horne AW, Greaves E. Endometriosis-associated macrophages:
origin, phenotype, and function. Front Endocrinol (Lausanne). 2020;11:7.
44. Capezzuoli T, Vannuccini S, Mautone D, Sorbi F, Chen H, Reis FM, et al.
Long-term hormonal treatment reduces repetitive surgery for endome‑
triosis recurrence. Reprod Biomed Online. 2021;42(2):451–6.
45. Cochrane Database Syst RevChen I, Veth VB, Choudhry AJ, Murji A,
Zakhari A, Black AY, et al. Pre‐ and postsurgical medical therapy for endo‑
metriosis surgery. Cochrane Database Syst Rev. 2020;2020(11):CD003678.
46. Chen I, Lalani S, Xie RH, Shen M, Singh SS, Wen SW. Association between
surgically diagnosed endometriosis and adverse pregnancy outcomes.
Fertil Steril. 2018;109(1):142–7.
47. Shafrir AL, Farland LV, Shah DK, Harris HR, Kvaskoff M, Zondervan K, et al.
Risk for and consequences of endometriosis: a critical epidemiologic
review. Best Pract Res Clin Obstet Gynaecol. 2018;51:1–15.
48. Gunawardena S, Dior UP, Cheng C, Healey M. New diagnosis of endome‑
triosis is less common in women over age forty presenting with pelvic
pain. J Minim Invasive Gynecol. 2021;28(4):891-8.e1.
49. Parasar P, Ozcan P, Terry KL. Endometriosis: epidemiology, diagnosis andclinical management. Curr Obstet Gynecol Rep. 2017;6(1):34–41.

Holdsworth‑Carson et al. BMC Medicine(2024) 22:320

50. Hemmert R, Schliep KC, Willis S, Peterson CM, Louis GB, Allen-Brady K,
et al. Modifiable life style factors and risk for incident endometriosis.
Paediatr Perinat Epidemiol. 2019;33(1):19–25.
51. Holdsworth-Carson SJ, Dior UP, Colgrave EM, Healey M, Montgomery GW,
Rogers PAW, et al. The association of body mass index with endometriosis
and disease severity in women with pain. J Endometr Pelvic Pain Disord.
2018;10(2):79–87.
52. Park S, Chung C. Differences in metabolic syndrome indicators by bodymass index of women with endometriosis. Nurs Open. 2021;8(6):3306–14.
53. Mu F, Rich-Edwards J, Rimm EB, Spiegelman D, Forman JP, Missmer SA.
Association between endometriosis and hypercholesterolemia or hyper‑
tension. Hypertension. 2017;70(1):59–65.
54. Mu F, Rich-Edwards J, Rimm EB, Spiegelman D, Missmer SA. Endometrio‑
sis and risk of coronary heart disease. Circ Cardiovasc Qual Outcomes.
2016;9(3):257–64.
55. Al-Ghamdi S, Shubair MM, El-Metwally A, Alsalamah M, Alshahrani SM,
Al-Khateeb BF, et al. The relationship between chronic pain, prehyperten‑
sion, and hypertension. A population-based cross-sectional survey in
Al-Kharj, Saudi Arabia. Postgrad Med. 2021;133(3):345–50.
56. Bruehl S, Chung OY, Jirjis JN, Biridepalli S. Prevalence of clinical hyperten‑sion in patients with chronic pain compared to nonpain general medical
patients. Clin J Pain. 2005;21(2):147–53.
57. Colafella KMM, Denton KM. Sex-specific differences in hypertension andassociated cardiovascular disease. Nat Rev Nephrol. 2018;14(3):185–201.
58. Shafrir AL, Wise LA, Palmer JR, Shuaib ZO, Katuska LM, Vinayak P, et al.
Validity of self-reported endometriosis: a comparison across four cohorts.
Hum Reprod. 2021;36(5):1268–78.
59. Saha R, Marions L, Tornvall P. Validity of self-reported endometriosis andendometriosis-related questions in a Swedish female twin cohort. Fertil
Steril. 2017;107(1):174-8 e2.
60. Rizk B, Fischer AS, Lotfy HA, Turki R, Zahed HA, Malik R, et al. Recur‑
rence of endometriosis after hysterectomy. Facts Views Vis Obgyn.
2014;6(4):219–27.
61. Long AJ, Kaur P, Lukey A, Allaire C, Kwon JS, Talhouk A, et al. Reoperationand pain-related outcomes after hysterectomy for endometriosis byoophorectomy status. Am J Obstet Gynecol. 2023;228(1):57.e1-.e18.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in pub‑lished maps and institutional affiliations.

Page 35 of 35